Prof. dr. C.G.M. (Cees) Snoek
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute
Bezoekadres
- Science Park 904
- Kamernummer: L4.56
Postadres
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Postbus 94323
1090 GH Amsterdam
Contactgegevens
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Publicaties
- refereed (199)
- wetenschappelijk (4)
- vakpublicatie (1)
- congresbijdragen (5)
- erkenning (16)
- supervised theses (3)
- datasets (3)
2023
Bagad, P., Tapaswi, M., & Snoek, C. G. M. (2023). Test of Time: Instilling Video-Language Models with a Sense of Time. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 2503-2516). IEEE Computer Society. https://doi.org/10.48550/arXiv.2301.02074, https://doi.org/10.1109/CVPR52729.2023.00247 [details]- Bernasco, W., Hoeben, E. M., Koelma, D., Liebst, L. S., Thomas, J., Appelman, J., Snoek, C. G. M., & Lindegaard, M. R. (2023). Promise Into Practice: Application of Computer Vision in Empirical Research on Social Distancing. Sociological Methods and Research, 52(3), 1239–1287. Advance online publication. https://doi.org/10.1177/00491241221099554 [details]
- Bhowmik, A., Wang, Y., Baka, N., Oswald, M. R., & Snoek, C. G. M. (2023). Detecting Objects with Context-Likelihood Graphs and Graph Refinement. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 6501-6510). IEEE Computer Society. https://doi.org/10.1109/ICCV51070.2023.00600 [details]
- Chen, S., Du, Y., Mettes, P., & Snoek, C. G. M. (2023). Multi-Label Meta Weighting for Long-Tailed Dynamic Scene Graph Generation. In ICMR'23: proceedings of the 2023 ACM International Conference on Multimedia Retrieval : Thessaloniki, Greece, June 12-15, 2023 (pp. 39-47). Association for Computing Machinery. https://doi.org/10.48550/arXiv.2306.10122, https://doi.org/10.1145/3591106.3592267 [details]
- Derakhshani, M. M., Sanchez, E., Bulat, A., Turrisi da Costa, V. G., Snoek, C. G. M., Tzimiropoulos, G., & Martinez, B. (2023). Bayesian Prompt Learning for Image-Language Model Generalization. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 15191-15200). IEEE Computer Society. https://doi.org/10.48550/arXiv.2210.02390, https://doi.org/10.1109/ICCV51070.2023.01398 [details]
- Du, Y., Shen, J., Zhen, X., & Snoek, C. G. M. (2023). EMO: Episodic Memory Optimization for Few-Shot Meta-Learning. In Conference on Lifelong Learning Agents
- Du, Y., Shen, J., Zhen, X., & Snoek, C. G. M. (2023). SuperDisco: Super-Class Discovery Improves Visual Recognition for the Long-Tail. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 19944-19954). IEEE Computer Society. https://doi.org/10.48550/arXiv.2304.00101, https://doi.org/10.1109/CVPR52729.2023.01910 [details]
- Du, Y., Xiao, Z., Liao, S., & Snoek, C. G. M. (2023). ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion. In 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://proceedings.neurips.cc/paper_files/paper/2023/hash/911dd89c81efc624c4e1c39381179505-Abstract-Conference.html
- Hu, T., Thong, W., Mettes, P., & Snoek, C. G. M. (2023). Query by Activity Video in the Wild. In 2023 IEEE International Conference on Image Processing (ICIP 2023) : Kuala Lumpur, Malaysia 8-11 October 2023 IEEE. https://doi.org/10.48550/arXiv.2311.13895
- Hu, V. T., Zhang, D. W., Asano, Y. M., Burghouts, G. J., & Snoek, C. G. M. (2023). Self-Guided Diffusion Models. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 18413-18422). IEEE Computer Society. https://doi.org/10.48550/arXiv.2210.06462, https://doi.org/10.1109/CVPR52729.2023.01766 [details]
- Jing, M., Li, J., Snoek, C., & Zhen, X. (2023). Variational Model Perturbation for Source-Free Domain Adaptation. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 23, pp. 17173-17187). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2022/hash/6d7a9f292360193eb530d693f7941c73-Abstract-Conference.html [details]
- Jing, M., Zhen, X., Li, J., & Snoek, C. G. M. (2023). Order-preserving Consistency Regularization for Domain Adaptation and Generalization. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 18870-18881). IEEE Computer Society. https://doi.org/10.48550/arXiv.2309.13258, https://doi.org/10.1109/ICCV51070.2023.01734 [details]
- Mirzaei, H., Salehidehnavi, S., Shahabi, S., Gavves, E., Snoek, C. G. M., Sabokrou, M., & Rohban, M. (2023). Fake It Until You Make It : Towards Accurate Near-Distribution Novelty Detection. In International Conference on Learning Representations
- Rastegar, S., Doughty, H. R., & Snoek, C. G. M. (2023). Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery. In 37th Conference on Neural Information Processing Systems (NeurIPS 2023) (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://proceedings.neurips.cc/paper_files/paper/2023/hash/e6789e468c65a7816760a00a487d3c4e-Abstract-Conference.html
- Salehi, M., Gavves, E., Snoek, C. G. M., & Asano, Y. M. (2023). Time Does Tell: Self-Supervised Time-Tuning of Dense Image Representations. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 16490-16501). IEEE Computer Society. https://doi.org/10.1109/ICCV51070.2023.01516, https://doi.org/10.48550/arXiv.2308.11796 [details]
- Shen, J., Snoek, C., Worring, M., Xiao, Z., & Zhen, X. (2023). Association Graph Learning for Multi-Task Classification with Category Shifts. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), 36th Conference on Neural Information Processing Systems (NeurIPS 2022): New Orleans, Louisiana, USA, 28 November-9 December 2022 (Vol. 7, pp. 4503-4516). (Advances in Neural Information Processing Systems; Vol. 35). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper_files/paper/2022/hash/1cc70be9fb6a83bc46cf4ac21a91e0b0-Abstract-Conference.html [details]
- Sun, H., Lu, X., Wang, H., Yin, Y., Zhen, X., Snoek, C. G. M., & Shao, L. (2023). Attentional prototype inference for few-shot segmentation. Pattern Recognition, 142, Article 109726. https://doi.org/10.1016/j.patcog.2023.109726 [details]
- Sun, W., Du, Y., Zhen, X., Wang, F., Wang, L., & Snoek, C. G. M. (2023). MetaModulation: Learning Variational Feature Hierarchies for Few-Shot Learning with Fewer Tasks. In International Conference on Machine Learning
- Thoker, F. M., Doughty, H., & Snoek, C. G. M. (2023). Tubelet-Contrastive Self-Supervision for Video-Efficient Generalization. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 13766-13777). IEEE Computer Society. https://doi.org/10.48550/arXiv.2303.11003, https://doi.org/10.1109/ICCV51070.2023.01270 [details]
- Xiao, Z., Zhen, X., Liao, S., & Snoek, C. G. M. (2023). Energy-Based Test Sample Adaptation for Domain Generalization. In International Conference on Learning Representations
- Yang, P., Snoek, C. G. M., & Asano, Y. M. (2023). Self-Ordering Point Clouds. In 2023 IEEE/CVF International Conference on Computer Vision: ICCV 2023 : Paris, France, 2-6 October 2023 : proceedings (pp. 15767-15776). IEEE Computer Society. https://doi.org/10.48550/arXiv.2304.00961, https://doi.org/10.1109/ICCV51070.2023.01449 [details]
- Zhang, Y., Doughty, H. R., & Snoek, C. G. M. (2023). Learning Unseen Modality Interaction. In Advances in Neural Information Processing Systems (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://proceedings.neurips.cc/paper_files/paper/2023/hash/abb4847bbd60f38b1b7649d26c7a0067-Abstract-Conference.html
- Zhang, Y., Zhang, W. D., Lacoste-Julien, S., Burghouts, G. J., & Snoek, C. G. M. (2023). Unlocking Slot Attention by Changing Optimal Transport Costs. In International Conference on Machine Learning
- van Sonsbeek, T., Derakhshani, M. M., Najdenkoska, I., Snoek, C. G. M., & Worring, M. (2023). Open-Ended Medical Visual Question Answering Through Prefix Tuning of Language Models. In H. Greenspan, A. Madabhushi, P. Mousavi, S. Salcudean, J. Duncan, T. Syeda-Mahmood, & R. Taylor (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2023: 26th International Conference, Vancouver, BC, Canada, October 8–12, 2023 : proceedings (Vol. V, pp. 726-736). (Lecture Notes in Computer Science; Vol. 14224). Springer. https://doi.org/10.48550/arXiv.2303.05977, https://doi.org/10.1007/978-3-031-43904-9_70 [details]
2022
- Derakhshani, M. M., Najdenkoska, I., van Sonsbeek, T., Zhen, X., Mahapatra, D., Worring, M., & Snoek, C. G. M. (2022). LifeLonger: A Benchmark for Continual Disease Classification. In L. Wang, Q. Dou, P. T. Fletcher, S. Speidel, & S. Li (Eds.), Medical Image Computing and Computer Assisted Intervention – MICCAI 2022: 25th International Conference, Singapore, September 18–22, 2022 : proceedings (Vol. II, pp. 314–324). (Lecture Notes in Computer Science; Vol. 13432). Springer. https://doi.org/10.48550/arXiv.2204.05737, https://doi.org/10.1007/978-3-031-16434-7_31 [details]
- Doughty, H., & Snoek, C. G. M. (2022). How Do You Do It? Fine-Grained Action Understanding with Pseudo-Adverbs. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 13822-13832). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.2203.12344, https://doi.org/10.1109/CVPR52688.2022.01346 [details]
- Du, Y., Zhen, X., Shao, L., & Snoek, C. G. M. (2022). Hierarchical Variational Memory for Few-shot Learning Across Domains. In International Conference on Learning Representations
- Nguyen, D-K., Yu, J., Booij, O., Oswald, M. R., & Snoek, C. G. M. (2022). BoxeR: Box-Attention for 2D and 3D Transformers. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 4763-4772). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.2111.13087, https://doi.org/10.1109/CVPR52688.2022.00473 [details]
- Shi, Z., Mettes, P., Maji, S., & Snoek, C. G. M. (2022). On Measuring and Controlling the Spectral Bias of the Deep Image Prior. International Journal of Computer Vision, 130(4), 885–908. Advance online publication. https://doi.org/10.1007/s11263-021-01572-7 [details]
- Thoker, F. M., Doughty, H., Bagad, P., & Snoek, C. G. M. (2022). How Severe is Benchmark-Sensitivity in Video Self-Supervised Learning? In S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, & T. Hassner (Eds.), Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 : proceedings (Vol. XXXIV, pp. 632–652). (Lecture Notes in Computer Science; Vol. 13694). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-19830-4_36 [details]
- Thong, W., & Snoek, C. G. M. (2022). Diversely-Supervised Visual Product Search. ACM Transactions on Multimedia Computing Communications and Applications, 18(1), Article 13. Advance online publication. https://doi.org/10.1145/3461646 [details]
- Xiao, Z., Zhen, X., Shao, L., & Snoek, C. G. M. (2022). Learning to generalize across domains on single test samples. In International Conference on Learning Representations
- Yang, P., Asano, Y. M., Mettes, P., & Snoek, C. G. M. (2022). Less than Few: Self-Shot Video Instance Segmentation. In S. Avidan, G. Brostow, M. Cissé, G. M. Farinella, & T. Hassner (Eds.), Computer Vision – ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23–27, 2022 : proceedings (Vol. XXXIV, pp. 449–466). (Lecture Notes in Computer Science; Vol. 13694). Springer. Advance online publication. https://doi.org/10.1007/978-3-031-19830-4_26 [details]
- Zhang, D. W., Burghouts, G. J., & Snoek, C. G. M. (2022). Pruning Edges and Gradients to Learn Hypergraphs from Larger Sets. Proceedings of Machine Learning Research, 198, Article 53. https://doi.org/10.48550/arXiv.2106.13919 [details]
- Zhang, Y., Doughty, H., Shao, L., & Snoek, C. G. M. (2022). Audio-Adaptive Activity Recognition Across Video Domains. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 13781-13790). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.2203.14240, https://doi.org/10.1109/CVPR52688.2022.01342 [details]
- Zhang, Y., Zhang, W. D., Lacoste-Julien, S., Burghouts, G. J., & Snoek, C. G. M. (2022). Multiset-Equivariant Set Prediction with Approximate Implicit Differentiation. In International Conference on Learning Representations
- Zhao, J., Zhang, Y., Li, X., Chen, H., Shuai, B., Xu, M., Liu, C., Kundu, K., Xiong, Y., Modolo, D., Marsic, I., Snoek, C. G. M., & Tighe, J. (2022). TubeR: Tubelet Transformer for Video Action Detection. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 13588-13597). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.2104.00969, https://doi.org/10.1109/CVPR52688.2022.01323 [details]
2021
- Appelman, J., Bijleveld, K., Ejbye-Ernst, P., Hoeben, E., Liebst, L., Snoek, C., Koelma, D., & Rosenkrantz Lindegaard, M. (2021). Naleving van gedragsmaatregelen tijdens de COVID-19-pandemie. Justitiële Verkenningen, 47(3), 54-71. https://doi.org/10.5553/JV/016758502021047003004 [details]
- Chen, S., Mettes, P., & Snoek, C. G. M. (2021). Diagnosing Errors in Video Relation Detectors. In 32nd British Machine Vision Conference 2021: BMVC 2021, Online, November 22-25, 2021 Article 241 BMVA Press. [details]
- Chen, S., Shi, Z., Mettes, P., & Snoek, C. G. M. (2021). Social fabric: Tubelet compositions for video relation detection. In 2021 IEEE/CVF International Conference on Computer Vision: proceedings : ICCV 2021 : 11-17 October 2021, virtual event (pp. 13465-13474). (International Conference on Computer Vision; Vol. 18). IEEE Computer Society. https://doi.org/10.1109/ICCV48922.2021.01323 [details]
- Derakhshani, M. M., Zhen, X., Shao, L., & Snoek, C. G. M. (2021). Kernel Continual Learning. Proceedings of Machine Learning Research, 139, 2621-2631. https://proceedings.mlr.press/v139/derakhshani21a.html [details]
- Du, Y., Holla, N., Zhen, X., Snoek, C. G. M., & Shutova, E. (2021). Meta-Learning with Variational Semantic Memory for Word Sense Disambiguation. In C. Zong, F. Xia, W. Li, & R. Navigli (Eds.), The 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing: ACL-IJCNLP 2021 : proceedings of the conference : August 1-6, 2021 (Vol. 1, pp. 5254-5268). The Association for Computational Linguistics. https://doi.org/10.18653/v1/2021.acl-long.409 [details]
- Du, Y., Zhen, X., Shao, L., & Snoek, C. G. M. (2021). MetaNorm: Learning to Normalize Few-Shot Batches Across Domains. In International Conference on Learning Representations (ICLR), 2021
- Gavrilyuk, K., Jain, M., Karmanov, I., & Snoek, C. G. M. (2021). Motion-Augmented Self-Training for Video Recognition at Smaller Scale. In 2021 IEEE/CVF International Conference on Computer Vision: proceedings : ICCV 2021 : 11-17 October 2021, virtual event (pp. 10409-10418). (International Conference on Computer Vision; Vol. 18). IEEE Computer Society. https://doi.org/10.1109/ICCV48922.2021.01026 [details]
- Klomp, S. R., van Rijn, M., Wijnhoven, R. G. J., Snoek, C. G. M., & de With, P. H. N. (2021). Safe Fakes: Evaluating Face Anonymizers for Face Detectors. In V. Štruc, & M. Ivanovska (Eds.), 2021 16th IEEE International Conference on Automatic Face and Gesture Recognition (FG 2021): Jodhpur, India (virtual event), December 15-18, 2021 : proceedings (pp. 121-128). Article 17 IEEE. https://doi.org/10.1109/FG52635.2021.9666936 [details]
- Liao, S., Gavves, E., Oh, C., & Snoek, C. G. M. (2021). Quasibinary Classifier for Images with Zero and Multiple Labels. In Proceedings of ICPR 2020: 25th International Conference on Pattern Recognition : Milan, 10-15 January 2021 (pp. 8743-8750). IEEE. https://doi.org/10.1109/ICPR48806.2021.9412933 [details]
- Mettes, P., Thong, W., & Snoek, C. G. M. (2021). Object priors for classifying and localizing unseen actions. International Journal of Computer Vision, 129(6), 1954–1971. Advance online publication. https://doi.org/10.1007/s11263-021-01454-y [details]
- Shi, Z., Chen, Y., Gavves, E., Mettes, P., & Snoek, C. G. M. (2021). Unsharp Mask Guided Filtering. IEEE Transactions on Image Processing, 30, 7472-7485. Advance online publication. https://doi.org/10.1109/TIP.2021.3106812 [details]
- Thoker, F. M., & Snoek, C. G. M. (2021). Feature-Supervised Action Modality Transfer. In Proceedings of ICPR 2020: 25th International Conference on Pattern Recognition : Milan, 10-15 January 2021 (pp. 3751-3758). IEEE. https://doi.org/10.1109/ICPR48806.2021.9412467 [details]
- Thoker, F. M., Doughty, H., & Snoek, C. G. M. (2021). Skeleton-Contrastive 3D Action Representation Learning. In MM '21: Proceedings of the 29th ACM International Conference on Multimedia : October 20-24, 2021, Virtual Event, China (pp. 1655-1663). Association for Computing Machinery. https://doi.org/10.1145/3474085.3475307 [details]
- Thong, W., & Snoek, C. G. M. (2021). Feature and Label Embedding Spaces Matter in Addressing Image Classifier Bias. In 32nd British Machine Vision Conference 2021: BMVC 2021, Online, November 22-25, 2021 Article 130 BMVA Press. [details]
- Wang, H., Yang, Y., Cao, X., Zhen, X., Snoek, C., & Shao, L. (2021). Variational prototype inference for few-shot semantic segmentation. In 2021 IEEE Winter Conference on Applications of Computer Vision: proceedings : 5-9 January 2021, virtual event (pp. 525-534). (WACV). IEEE Computer Society. https://doi.org/10.1109/WACV48630.2021.00057 [details]
- Xiao, Z., Shen, J., Zhen, X., Shao, L., & Snoek, C. G. M. (2021). A Bit More Bayesian: Domain-Invariant Learning with Uncertainty. Proceedings of Machine Learning Research, 139, 11351-11361. https://proceedings.mlr.press/v139/xiao21a.html [details]
- Yang, P., Mettes, P., & Snoek, C. G. M. (2021). Few-Shot Transformation of Common Actions into Time and Space. In Proceedings, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition: virtual, 9-25 June 2021 (pp. 16026-16035). (CVPR). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.48550/arXiv.2104.02439, https://doi.org/10.1109/CVPR46437.2021.01577 [details]
- Zhang, W. D., Burghouts, G. J., & Snoek, C. G. M. (2021). Set Prediction without Imposing Structure as Conditional Density Estimation. In International Conference on Learning Representations
- Zhang, Y., Shao, L., & Snoek, C. G. M. (2021). Repetitive Activity Counting by Sight and Sound. In Proceedings, 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition: virtual, 9-25 June 2021 (pp. 14065-14074). (CVPR). Conference Publishing Services, IEEE Computer Society. https://doi.org/10.48550/arXiv.2103.13096, https://doi.org/10.1109/CVPR46437.2021.01385 [details]
- Zhao, J., & Snoek, C. G. M. (2021). LiftPool: Bidirectional ConvNet Pooling. In International Conference on Learning Representations
- Zhen, X., Du, Y., Xiong, H., Qiu, Q., Snoek, C., & Shao, L. (2021). Learning to Learn Variational Semantic Memory. In H. Larochelle, M. Ranzato, R. Hadsell, M. F. Balcan, & H. Lin (Eds.), 34th Concerence on Neural Information Processing Systems (NeurIPS 2020): online, 6-12 December 2020 (Vol. 11, pp. 9122-9134). (Advances in Neural Information Processing Systems; Vol. 33). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2020/hash/67d16d00201083a2b118dd5128dd6f59-Abstract.html [details]
2020
- Chen, S., Mettes, P., Hu, T., & Snoek, C. G. M. (2020). Interactivity Proposals for Surveillance Videos. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 108-116). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390680 [details]
- Chen, Y., Hu, V. T., Gavves, E., Mensink, T., Mettes, P., Yang, P., & Snoek, C. G. M. (2020). PointMixup: Augmentation for Point Clouds. In A. Vedaldi, H. Bischof, T. Brox, & J. M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. III, pp. 330-345). (Lecture Notes in Computer Science; Vol. 12348). Springer. https://doi.org/10.1007/978-3-030-58580-8_20 [details]
- Du, Y., Xu, J., Xiong, H., Qiu, Q., Zhen, X., Snoek, C. G. M., & Shao, L. (2020). Learning to Learn with Variational Information Bottleneck for Domain Generalization. In A. Vedaldi, H. Bischof, T. Brox, & J. M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. X, pp. 200-216). (Lecture Notes in Computer Science; Vol. 12355). Springer. https://doi.org/10.1007/978-3-030-58607-2_12 [details]
- Escorcia, V., Dao, C. D., Jain, M., Ghanem, B., & Snoek, C. (2020). Guess Where? Actor-Supervision for Spatiotemporal Video Action Localization. Computer Vision and Image Understanding, 192, Article 102886. Advance online publication. https://doi.org/10.1016/j.cviu.2019.102886 [details]
- Gavrilyuk, K., Sanford, R., Javan, M., & Snoek, C. G. M. (2020). Actor-Transformers for Group Activity Recognition. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : virtual, 14-19 June 2020 (pp. 836-845). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR42600.2020.00092 [details]
- Jain, M., Ghodrati, A., & Snoek, C. G. M. (2020). ActionBytes: Learning from Trimmed Videos to Localize Actions. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : virtual, 14-19 June 2020 (pp. 1168-1177). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR42600.2020.00125 [details]
- Long, T., Mettes, P., Shen, H. T., & Snoek, C. (2020). Searching for Actions on the Hyperbole. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : virtual, 14-19 June 2020 (pp. 1138-1147). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR42600.2020.00122 [details]
- Mettes, P., Koelma, D. C., & Snoek, C. G. M. (2020). Shuffled ImageNet Banks for Video Event Detection and Search. ACM Transactions on Multimedia Computing Communications and Applications, 16(2), Article 44. Advance online publication. https://doi.org/10.1145/3377875 [details]
- Mettes, P., Van Der Pol, E., & Snoek, C. (2020). Hyperspherical Prototype Networks. In H. Wallach, H. Larochelle, A. Beygelzimer, F. d'Alché-Buc, E. Fox, & R. Garnett (Eds.), 32nd Conference on Neural Information Processing Systems (NeurIPS 2019): Vancouver, Canada, 8-14 December 2019 (pp. 1476-1486). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/02a32ad2669e6fe298e607fe7cc0e1a0-Abstract.html [details]
- Narayan, S., Gupta, A., Khan, F. S., Snoek, C. G. M., & Shao, L. (2020). Latent Embedding Feedback and Discriminative Features for Zero-Shot Classification. In A. Vedaldi, H. Bischof, T. Brox, & J-M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. XXII, pp. 479-495). (Lecture Notes in Computer Science; Vol. 12367). Springer. https://doi.org/10.1007/978-3-030-58542-6_29 [details]
- Runia, T. F. H., Gavrilyuk, K., Snoek, C. G. M., & Smeulders, A. W. M. (2020). Cloth in the Wind: A Case Study of Physical Measurement through Simulation. In 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : virtual, 14-19 June 2020 (pp. 10495-10504). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR42600.2020.01051 [details]
- Thong, W., & Snoek, C. G. M. (2020). Bias-Awareness for Zero-Shot Learning the Seen and Unseen. In 31st British Machine Vision Conference 2020: BMVC 2020, Virtual Event, UK, September 7-10, 2020 Article 261 BMVA Press. [details]
- Thong, W., Mettes, P., & Snoek, C. G. M. (2020). Open Cross-Domain Visual Search. Computer Vision and Image Understanding, 200, Article 103045. Advance online publication. https://doi.org/10.1016/j.cviu.2020.103045 [details]
- Yang, P., Hu, V. T., Mettes, P., & Snoek, C. G. M. (2020). Localizing the Common Action Among a Few Videos. In A. Vedaldi, H. Bischof, T. Brox, & J-M. Frahm (Eds.), Computer Vision – ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020 : proceedings (Vol. VII, pp. 505-521). (Lecture Notes in Computer Science; Vol. 12352). Springer. https://doi.org/10.1007/978-3-030-58571-6_30 [details]
- Zhao, J., Han, J., Shao, L., & Snoek, C. G. M. (2020). Pixelated Semantic Colorization. International Journal of Computer Vision, 128(4), 818–834. Advance online publication. https://doi.org/10.1007/s11263-019-01271-4 [details]
- Zhen, X., Sun, H., Du, Y., Xu, J., Yin, Y., Shao, L., & Snoek, C. (2020). Learning to learn kernels with variational random features. Proceedings of Machine Learning Research, 119, 11409-11419. https://doi.org/10.48550/arXiv.2006.06707 [details]
2019
- Cappallo, S., Svetlichnaya, S., Garrigues, P., Mensink, T., & Snoek, C. G. M. (2019). New Modality: Emoji Challenges in Prediction, Anticipation, and Retrieval. IEEE Transactions on Multimedia, 21(2), 402-415. Advance online publication. https://doi.org/10.1109/TMM.2018.2862363 [details]
- Hu, T., Mettes, P., Huang, J-H., & Snoek, C. G. M. (2019). SILCO: Show a Few Images, Localize the Common Object. In Proceedings, 2019 International Conference on Computer Vision: 27 October-2 November 2019, Seoul, Korea (pp. 5066-5075). (ICCV). IEEE Computer Society. https://doi.org/10.1109/ICCV.2019.00517 [details]
- Hu, T., Yang, P., Zhang, C., Yu, G., Mu, Y., & Snoek, C. G. M. (2019). Attention-based Multi-Context Guiding for Few-Shot Semantic Segmentation. In Thirty-Third AAAI Conference on Artificial Intelligence, Thirty-First Conference on Innovative Applications of Artificial Intelligence, The Ninth Symposium on Educational Advances in Artificial Intelligence: AAAI-19, IAAI-19, EAAI-20 : January 27-February 1, 2019, Hilton Hawaiian Village, Honolulu, Hawaii, USA (pp. 8441-8448). (Proceedings of the AAAI Conference on Artificial Intelligence; Vol. 33). AAAI Press. https://doi.org/10.1609/aaai.v33i01.33018441 [details]
- Liao, S., Gavves, E., & Snoek, C. G. M. (2019). Spherical Regression: Learning Viewpoints, Surface Normals and 3D Rotations on n-Spheres. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 16-20 June 2019, Long Beach, California (pp. 9751-9759). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.1904.05404, https://doi.org/10.1109/CVPR.2019.00999 [details]
- Mettes, P., & Snoek, C. G. M. (2019). Pointly-Supervised Action Localization. International Journal of Computer Vision, 127(3), 263–281. Advance online publication. https://doi.org/10.1007/s11263-018-1120-4 [details]
- Runia, T. F. H., Snoek, C. G. M., & Smeulders, A. W. M. (2019). Repetition Estimation. International Journal of Computer Vision, 127(9), 1361–1383. Advance online publication. https://doi.org/10.1007/s11263-019-01194-0 [details]
- Shi, Z., Mettes, P., & Snoek, C. G. M. (2019). Counting with Focus for Free. In Proceedings, 2019 International Conference on Computer Vision: 27 October-2 November 2019, Seoul, Korea (pp. 4199-4208). (ICCV). IEEE Computer Society. https://doi.org/10.1109/ICCV.2019.00430 [details]
- Zhao, J., & Snoek, C. G. M. (2019). Dance with Flow: Two-in-One Stream Action Detection. In 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 16-20 June 2019, Long Beach, California (pp. 9927-9936). (CVPR). IEEE Computer Society. https://doi.org/10.48550/arXiv.1904.00696, https://doi.org/10.1109/CVPR.2019.01017 [details]
2018
- Dong, J., Li, X., & Snoek, C. G. M. (2018). Predicting Visual Features from Text for Image and Video Caption Retrieval. IEEE Transactions on Multimedia, 20(12), 3377-3388. Advance online publication. https://doi.org/10.1109/TMM.2018.2832602 [details]
- Gavrilyuk, K., Ghodrati, A., Li, Z., & Snoek, C. G. M. (2018). Actor and Action Video Segmentation From a Sentence. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 18-22 June 2018, Salt Lake City, Utah (pp. 5958-5966). IEEE Computer Society. https://doi.org/10.1109/CVPR.2018.00624 [details]
- Ghodrati, A., Gavves, E., & Snoek, C. G. M. (2018). Video Time: Properties, Encoders and Evaluation. In British Machine Vision Conference 2018: BMVC 2018, Newcastle, UK, September 3-6, 2018 Article 859 BMVA Press. [details]
- Li, Z., Gavrilyuk, K., Gavves, E., Jain, M., & Snoek, C. G. M. (2018). VideoLSTM Convolves, Attends and Flows for Action Recognition. Computer Vision and Image Understanding, 166, 41-50. Advance online publication. https://doi.org/10.1016/j.cviu.2017.10.011 [details]
- Liao, S., Gavves, E., & Snoek, C. G. M. (2018). Searching and Matching Texture-free 3D Shapes in Images. In ICMR'18: proceedings of the 2018 ACM International Conference on Multimedia Retrieval : June 11-14, 2018, Yokohama, Japan (pp. 326-334). The Association for Computing Machinery. https://doi.org/10.1145/3206025.3206057 [details]
- Migut, G., Koelma, D., Snoek, C. G. M., & Brouwer, N. (2018). Cheat me not: automated proctoring of digital exams on Bring-Your-Own-Device. In I. Polycarpou, J. C. Read, P. Andreou, & M. Armoni (Eds.), ITiCSE'18: proceedings of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education : July 2-4, 2018, Larnaca, Cyprus (pp. 388). The Association for Computing Machinery. https://doi.org/10.1145/3197091.3205813 [details]
- Runia, T. F. H., Snoek, C. G. M., & Smeulders, A. W. M. (2018). Primitive Motion Types for Learning from Instructional Video. In FIVER @ CVPR 2018: abstracts CVPR 2018. [details]
- Runia, T. F. H., Snoek, C. G. M., & Smeulders, A. W. M. (2018). Real-World Repetition Estimation by Div, Grad and Curl. In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition: proceedings : 18-22 June 2018, Salt Lake City, Utah (pp. 9009-9017). IEEE Computer Society. https://doi.org/10.1109/CVPR.2018.00939 [details]
- Zhao, J., Liu, L., Snoek, C. G. M., Han, J., & Shao, L. (2018). Pixel-level Semantics Guided Image Colorization. In British Machine Vision Conference 2018: BMVC 2018, Newcastle, UK, September 3-6, 2018 Article 236 BMVA Press. [details]
2017
- Cappallo, S., & Snoek, C. G. M. (2017). Future-Supervised Retrieval of Unseen Queries for Live Video. In MM'17: proceedings of the 2017 ACM Multimedia Conference : October 23-27, 2017, Mountain View, CA, USA (pp. 28-36). Association for Computing Machinery. https://doi.org/10.1145/3123266.3123437 [details]
- Habibian, A., Mensink, T., & Snoek, C. G. M. (2017). Video2vec Embeddings Recognize Events when Examples are Scarce. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39(10), 2089-2103. Advance online publication. https://doi.org/10.1109/TPAMI.2016.2627563 [details]
- Jain, M., van Gemert, J., Jégou, H., Bouthemy, P., & Snoek, C. G. M. (2017). Tubelets: Unsupervised Action Proposals from Spatiotemporal Super-Voxels. International Journal of Computer Vision, 124(3), 287-311. Advance online publication. https://doi.org/10.1007/s11263-017-1023-9 [details]
- Li, X., Uricchio, T., Ballan, L., Bertini, M., Snoek, C. G. M., & Del Bimbo, A. (2017). Socializing the Semantic Gap: A Comparative Survey on Image Tag Assignment, Refinement and Retrieval. ACM Computing Surveys, 49(1), Article 14. Advance online publication. https://doi.org/10.1145/2906152 [details]
- Li, Z., Tao, R., Gavves, E., Snoek, C. G. M., & Smeulders, A. W. M. (2017). Tracking by Natural Language Specification. In 30th IEEE Conference on Computer Vision and Pattern Recognition: CVPR 2017 : 21-26 July 2016, Honolulu, Hawaii : proceedings (pp. 7350-7358). IEEE. https://doi.org/10.1109/CVPR.2017.777 [details]
- Mensink, T., Jongstra, T., Mettes, P., & Snoek, C. G. M. (2017). Music-Guided Video Summarization using Quadratic Assignments. In ICMR '17: proceedings of the 2017 ACM International Conference on Multimedia Retrieval : June 6-9, 2017, Bucharest, Romania (pp. 58-64). The Association for Computing Machinery. https://doi.org/10.1145/3078971.3079024 [details]
- Mettes, P., & Snoek, C. G. M. (2017). Spatial-Aware Object Embeddings for Zero-Shot Localization and Classification of Actions. In 2017 IEEE International Conference on Computer Vision : ICCV 2017: proceedings : 22-29 October 2017, Venice, Italy (pp. 4453-4462). IEEE Computer Society. https://doi.org/10.1109/ICCV.2017.476 [details]
- Mettes, P., Snoek, C. G. M., & Chang, S-F. (2017). Localizing Actions from Video Labels and Pseudo-Annotations. In T. K. Kim, S. Zafeiriou, G. Brostow, & K. Mikolajczyk (Eds.), Proceedings of the British Machine Vision Conference 2017 Article 22 BMVA Press. https://doi.org/10.5244/C.31.22 [details]
2016
- Agharwal, A., Kovvuri, R., Nevatia, R., & Snoek, C. G. M. (2016). Tag-based Video Retrieval by Embedding Semantic Content in a Continuous Word Space. In 2016 IEEE Winter Conference on Applications of Computer Vision: WACV 2016: Lake Placid, New York, USA, 7-10 March 2016 (pp. 1354-1361). IEEE. https://doi.org/10.1109/WACV.2016.7477706 [details]
- Awad, G., Snoek, C. G. M., Smeaton, A. F., & Quénot, G. (2016). TRECVid Semantic Indexing of Video: A 6-year Retrospective. ITE Transactions on Media Technology and Applications, 4(3), 187-208. https://doi.org/10.3169/mta.4.187 [details]
- Bal, H., Epema, D., de Laat, C., van Nieuwpoort, R., Romein, J., Seinstra, F., Snoek, C., & Wijshoff, H. (2016). A Medium-Scale Distributed System for Computer Science Research: Infrastructure for the Long Term. Computer, 49(5), 54-63. https://doi.org/10.1109/MC.2016.127 [details]
- Cappallo, S., Mensink, T., & Snoek, C. G. M. (2016). Video Stream Retrieval of Unseen Queries using Semantic Memory. In R. C. Wilson, E. R. Hancock, & W. A. P. Smith (Eds.), Proceedings of the British Machine Vision Conference: BMVC 2016 Article 143 BMVA Press. https://doi.org/10.5244/C.30.143 [details]
- De Geest, R., Gavves, E., Ghodrati, A., Li, Z., Snoek, C., & Tuytelaars, T. (2016). Online Action Detection. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016 : proceedings (Vol. 5, pp. 269-284). (Lecture Notes in Computer Science; Vol. 9909). Springer. https://doi.org/10.1007/978-3-319-46454-1_17 [details]
- Dong, J., Li, X., Lan, W., Huo, Y., & Snoek, C. G. M. (2016). Early Embedding and Late Reranking for Video Captioning. In MM’16 : proceedings of the 2016 ACM Multimedia Conference (pp. 1082-1086). Association for Computing Machinery. https://doi.org/10.1145/2964284.2984064 [details]
- Kordumova, S., Mensink, T., & Snoek, C. G. M. (2016). Pooling Objects for Recognizing Scenes without Examples. In ICMR'16: proceedings of the 2016 ACM International Conference on Multimedia Retrieval: June 6-9, 2016, New York, NY, USA (pp. 143-150). Association for Computing Machinery. https://doi.org/10.1145/2911996.2912007 [details]
- Kordumova, S., van Gemert, J., & Snoek, C. G. M. (2016). Exploring the Long Tail of Social Media Tags. In Q. Tian, N. Sebe, G-J. Qi, B. Huet, R. Hong, & X. Liu (Eds.), MultiMedia Modeling: 22nd International Conference, MMM 2016: Miami, FL, USA, January 4-6, 2016: proceedings (Vol. 1, pp. 51-62). (Lecture Notes in Computer Science; Vol. 9516). Springer. https://doi.org/10.1007/978-3-319-27671-7_5 [details]
- Kovvuri, R., Nevatia, R., & Snoek, C. G. M. (2016). Segment-based Models for Event Detection and Recounting. In 2016 23rd International Conference on Pattern Recognition: ICPR 2016 : Cancún, México, 4-8 December 2016 (pp. 3868-3873). IEEE. https://doi.org/10.1109/ICPR.2016.7900238 [details]
- Mazloom, M., Li, X., & Snoek, C. G. M. (2016). TagBook: A Semantic Video Representation without Supervision for Event Detection. IEEE Transactions on Multimedia, 18(7), 1378-1388. https://doi.org/10.1109/TMM.2016.2559947 [details]
- Mettes, P., Koelma, D. C., & Snoek, C. G. M. (2016). The ImageNet Shuffle: Reorganized Pre-training for Video Event Detection. In ICMR'16: proceedings of the 2016 ACM International Conference on Multimedia Retrieval: June 6-9, 2016, New York, NY, USA (pp. 175-182). Association for Computing Machinery. https://doi.org/10.1145/2911996.2912036 [details]
- Mettes, P., van Gemert, J. C., & Snoek, C. G. M. (2016). No Spare Parts: Sharing Part Detectors for Image Categorization. Computer Vision and Image Understanding, 152, 131-141. Advance online publication. https://doi.org/10.1016/j.cviu.2016.07.008 [details]
- Mettes, P., van Gemert, J. C., & Snoek, C. G. M. (2016). Spot On: Action Localization from Pointly-Supervised Proposals. In B. Leibe, J. Matas, N. Sebe, & M. Welling (Eds.), Computer Vision – ECCV 2016: 14th European Conference, Amsterdam, The Netherlands, October 11-14, 2016 : proceedings (Vol. 5, pp. 437-453). (Lecture Notes in Computer Science; Vol. 9909). Springer. https://doi.org/10.1007/978-3-319-46454-1_27 [details]
- Sang, J., Gao, Y., Bao, B., Snoek, C., & Dai, Q. (2016). Recent advances in social multimedia big data mining and applications. Multimedia Systems, 22(1), 1-3. Advance online publication. https://doi.org/10.1007/s00530-015-0482-5 [details]
- Zhang, L., Ji, R., Yi, Z., Lin, W., & Snoek, C. (2016). Special issue on weakly supervised learning. Journal of Visual Communication and Image Representation, 37, 1-2. Advance online publication. https://doi.org/10.1016/j.jvcir.2016.02.012 [details]
2015
- Cappallo, S., Mensink, T., & Snoek, C. G. M. (2015). Image2Emoji: Zero-shot Emoji Prediction for Visual Media. In MM'15: proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015, Brisbane, Australia (pp. 1311-1314). Association for Computing Machinery. https://doi.org/10.1145/2733373.2806335 [details]
- Cappallo, S., Mensink, T., & Snoek, C. G. M. (2015). Latent Factors of Visual Popularity Prediction. In ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China (pp. 195-202). Association for Computing Machinery. https://doi.org/10.1145/2671188.2749405 [details]
- Cappallo, S., Mensink, T., & Snoek, C. G. M. (2015). Query-by-Emoji Video Search. In MM'15: proceedings of the 2015 ACM Multimedia Conference: October 26-30, 2015, Brisbane, Australia (pp. 735-736). Association for Computing Machinery. https://doi.org/10.1145/2733373.2807961 [details]
- Gavves, E., Fernando, B., Snoek, C. G. M., Smeulders, A. W. M., & Tuytelaars, T. (2015). Local Alignments for Fine-Grained Categorization. International Journal of Computer Vision, 111(2), 191-212. Advance online publication. https://doi.org/10.1007/s11263-014-0741-5 [details]
- Gavves, E., Mensink, T., Tommasi, T., Snoek, C. G. M., & Tuytelaars, T. (2015). Active Transfer Learning with Zero-Shot Priors: Reusing Past Datasets for Future Tasks. In Proceedings: 2015 IEEE International Conference on Computer Vision: 11-18 December 2015, Santiago, Chile (pp. 2731-2739). IEEE Computer Society. https://doi.org/10.1109/ICCV.2015.313 [details]
- Habibian, A., Mensink, T., & Snoek, C. G. M. (2015). Discovering Semantic Vocabularies for Cross-Media Retrieval. In ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China (pp. 131-138). Association for Computing Machinery. https://doi.org/10.1145/2671188.2749403 [details]
- Jain, M., van Gemert, J. C., & Snoek, C. G. M. (2015). What do 15,000 object categories tell us about classifying and localizing actions? In 2015 IEEE Conference on Computer Vision and Pattern Recognition: 7-12 June 2015, Boston, MA (pp. 46-55). IEEE. https://doi.org/10.1109/CVPR.2015.7298599 [details]
- Jain, M., van Gemert, J. C., Mensink, T., & Snoek, C. G. M. (2015). Objects2action: Classifying and localizing actions without any video example. In Proceedings: 2015 IEEE International Conference on Computer Vision: 11-18 December 2015, Santiago, Chile (pp. 4588-4596). IEEE Computer Society. https://doi.org/10.1109/ICCV.2015.521 [details]
- Kordumova, S., Li, X., & Snoek, C. G. M. (2015). Best Practices for Learning Video Concept Detectors from Social Media Examples. Multimedia Tools and Applications, 74(4), 1291-1315. Advance online publication. https://doi.org/10.1007/s11042-014-2056-5 [details]
- Mazloom, M., Habibian, A., Liu, D., Snoek, C. G. M., & Chang, S. F. (2015). Encoding Concept Prototypes for Video Event Detection and Summarization. In ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China (pp. 123-130). Association for Computing Machinery. https://doi.org/10.1145/2671188.2749402 [details]
- Mettes, P., van Gemert, J. C., Cappallo, S., Mensink, T., & Snoek, C. G. M. (2015). Bag-of-Fragments: Selecting and encoding video fragments for event detection and recounting. In ICMR'15: proceedings of the 2015 ACM International Conference on Multimedia Retrieval: June 23-26, 2015, Shanghai, China (pp. 427-434). Association for Computing Machinery. https://doi.org/10.1145/2671188.2749404 [details]
- Nagel, M., Mensink, T., & Snoek, C. G. M. (2015). Event Fisher Vectors: Robust Encoding Visual Diversity of Visual Streams. In X. Xie, M. W. Jones, & G. K. L. Tam (Eds.), Proceedings of the British Machine Vision Conference 2015: BMVC 2015: 7-10 September, Swansea, UK Article 178 BMVA Press. https://doi.org/10.5244/C.29.178 [details]
- Snoek, C. G. M., Cappallo, S., Fontijne, D., Julian, D., Koelma, D. C., Mettes, P., van de Sande, K. E. A., Sarah, A., Stokman, H., & Towal, R. B. (2015). Qualcomm Research and University of Amsterdam at TRECVID 2015: Recognizing Concepts, Objects, and Events in Video. In 2015 TREC Video Retrieval Evaluation: notebook papers and slides National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv15.papers/mediamill.pdf [details]
- van Gemert, J. C., Jain, M., Gati, E., & Snoek, C. G. M. (2015). APT: Action localization Proposals from dense Trajectories. In X. Xie, M. W. Jones, & G. K. L. Tam (Eds.), Proceedings of the British Machine Vision Conference 2015: BMVC 2015: 7-10 September, Swansea, UK Article 177 BMVA Press. https://doi.org/10.5244/C.29.177 [details]
2014
- Del Bimbo, A., Candan, K. S., J., Y-G., Luo, J., Mei, T., Sebe, N., Shen, H. T., Snoek, C. G. M., & Yan, R. (2014). Guest editorial: Special Section on Socio-Mobile Media Analysis and Retrieval. IEEE Transactions on Multimedia, 16(3), 586-587. https://doi.org/10.1109/TMM.2014.2304314 [details]
- Habibian, A., & Snoek, C. G. M. (2014). Recommendations for Recognizing Video Events by Concept Vocabularies. Computer Vision and Image Understanding, 124, 110-122. https://doi.org/10.1016/j.cviu.2014.02.003 [details]
- Habibian, A., & Snoek, C. G. M. (2014). Stop-Frame Removal Improves Web Video Classification. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 499-502). Association for Computing Machinery. https://doi.org/10.1145/2578726.2578803 [details]
- Habibian, A., Mazloom, M., & Snoek, C. G. M. (2014). On-the-Fly Video Event Search by Semantic Signatures. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 518-521). Association for Computing Machinery. https://doi.org/10.1145/2578726.2582615 [details]
- Habibian, A., Mensink, T., & Snoek, C. G. M. (2014). Composite Concept Discovery for Zero-Shot Video Event Detection. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 17-24). Association for Computing Machinery. https://doi.org/10.1145/2578726.2578746 [details]
- Habibian, A., Mensink, T., & Snoek, C. G. M. (2014). VideoStory: A New Multimedia Embedding for Few-Example Recognition and Translation of Events. In MM '14: proceedings of the 2014 ACM Conference on Multimedia: November 3-7, 2014, Orlando, Florida, USA (pp. 17-26). ACM. https://doi.org/10.1145/2647868.2654913 [details]
- Jain, M., van Gemert, J., & Snoek, C. G. M. (2014). University of Amsterdam at THUMOS Challenge 2014. In THUMOS Challenge 2014: notebook papers Center for Research in Computer Vision, University of Central Florida. http://crcv.ucf.edu/THUMOS14/papers/University%20of%20Amesterdam.pdf [details]
- Jain, M., van Gemert, J., Jégou, H., Bouthemy, P., & Snoek, C. G. M. (2014). Action Localization by Tubelets from Motion. In Proceedings: 2014 IEEE Conference on Computer Vision and Pattern Recognition: 23-28 June 2014, Columbus, Ohio (pp. 740-747). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.100 [details]
- Kordumova, S., Kofler, C., Koelma, D. C., Huurnink, B., Freiburg, B., Kleinveld, J., van Rijn, M., van Deursen, M., Larson, M., & Snoek, C. G. M. (2014). SocialZap: Catch-Up on Interesting Television Fragments Discovered from Social Media. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 538-540). Association for Computing Machinery. https://doi.org/10.1145/2578726.2582622 [details]
- Li, Z., Gavves, E., Mensink, T., & Snoek, C. G. M. (2014). Attributes Make Sense on Segmented Objects. In D. Fleet, T. Pajdla, B. Schiele, & T. Tuytelaars (Eds.), Computer Vision – ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6-12, 2014: proceedings (Vol. VI, pp. 350-365). (Lecture Notes in Computer Science; Vol. 8694). Springer. https://doi.org/10.1007/978-3-319-10599-4_23 [details]
- Mazloom, M., Gavves, E., & Snoek, C. G. M. (2014). Conceptlets: Selective Semantics for Classifying Video Events. IEEE Transactions on Multimedia, 16(8), 2214-2228. https://doi.org/10.1109/TMM.2014.2359771 [details]
- Mazloom, M., Li, X., & Snoek, C. G. M. (2014). Few-Example Video Event Retrieval Using Tag Propagation. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 459-462). Association for Computing Machinery. https://doi.org/10.1145/2578726.2578793 [details]
- Mensink, T., Gavves, E., & Snoek, C. G. M. (2014). COSTA: Co-Occurrence Statistics for Zero-Shot Classification. In Proceedings: 2014 IEEE Conference on Computer Vision and Pattern Recognition: 23-28 June 2014, Columbus, Ohio (pp. 2441-2448). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.313 [details]
- Myers, G. K., Nallapati, R., van Hout, J., Pancoast, S., Nevatia, R., Sun, C., Habibian, A., Koelma, D. C., van de Sande, K. E. A., Smeulders, A. W. M., & Snoek, C. G. M. (2014). Evaluating Multimedia Features and Fusion for Example-Based Event Detection. Machine Vision and Applications, 25(1), 17-32. https://doi.org/10.1007/s00138-013-0527-8 [details]
- Snoek, C. G. M., van de Sande, K. E. A., Fontijne, D., Cappallo, S., van Gemert, J., Habibian, A., Mensink, T., Mettes, P., Tao, R., Koelma, D. C., & Smeulders, A. W. M. (2014). MediaMill at TRECVID 2014: Searching Concepts, Objects, Instances and Events in Video. In 2014 TREC Video Retrieval Evaluation: notebook papers and slides National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv14.papers/mediamill.pdf [details]
- Sun, C., Burns, B., Nevatia, R., Snoek, C., Bolles, B., Myers, G., Wang, W., & Yeh, E. (2014). ISOMER: Informative Segment Observations for Multimedia Event Recounting. In ICMR Glasgow 2014: proceedings of the ACM International Conference on Multimedia Retrieval 2014: April 1st-4th, 2014, Glasgow, UK (pp. 241-248). Association for Computing Machinery. https://doi.org/10.1145/2578726.2578757 [details]
- Tao, R., Gavves, E., Snoek, C. G. M., & Smeulders, A. W. M. (2014). Locality in Generic Instance Search from One Example. In Proceedings: 2014 IEEE Conference on Computer Vision and Pattern Recognition: 23-28 June 2014, Columbus, Ohio (pp. 2099-2106). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.269 [details]
- Xie, L., Shamma, D. A., & Snoek, C. (2014). Content is Dead ... Long Live Content: The New Age of Multimedia-Hard Problems. IEEE Multimedia, 21(1), 4-8. https://doi.org/10.1109/MMUL.2014.5 [details]
- Yang, Y., Sebe, N., Snoek, C., Hua, X. S., & Zhuang, Y. (2014). Special Section on Learning from Multiple Evidences for Large Scale Multimedia Analysis: editorial. Computer Vision and Image Understanding, 118, 1. https://doi.org/10.1016/j.cviu.2013.09.001 [details]
- van Hout, J., Yeh, E., Koelma, D. C., Snoek, C. G. M., Sun, C., Nevatia, R., Wong, J., & Myers, G. K. (2014). Late Fusion and Calibration for Multimedia Event Detection Using Few Examples. In 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 4598-4602). IEEE. https://doi.org/10.1109/ICASSP.2014.6854473 [details]
- van de Sande, K. E. A., Snoek, C. G. M., & Smeulders, A. W. M. (2014). Fisher and VLAD with FLAIR. In Proceedings: 2014 IEEE Conference on Computer Vision and Pattern Recognition: 23-28 June 2014, Columbus, Ohio (pp. 2377-2384). IEEE Computer Society. https://doi.org/10.1109/CVPR.2014.304 [details]
2013
- Gavves, E., Fernando, B., Snoek, C. G. M., Smeulders, A. W. M., & Tuytelaars, T. (2013). Fine-Grained Categorization by Alignments. In 2013 IEEE International Conference on Computer Vision: ICCV 2013 : proceedings: 1-8 December 2013, Sydney, NSW, Australia (pp. 1713-1720). IEEE Computer Society. https://doi.org/10.1109/ICCV.2013.215 [details]
- Habibian, A., & Snoek, C. G. M. (2013). Video2Sentence and Vice Versa. In MM '13: proceedings of the 2013 ACM Multimedia Conference : October 21-25, 2013, Barcelona, Spain (Vol. 1, pp. 419-420). ACM. https://doi.org/10.1145/2502081.2502249 [details]
- Habibian, A., van de Sande, K. E. A., & Snoek, C. G. M. (2013). Recommendations for Video Event Recognition Using Concept Vocabularies. In ICMR'13: proceedings of the third ACM International Conference on Multimedia Retrieval : April 16-20, 2013, Dallas, Texas, USA (pp. 89-96). Association for Computing Machinery. https://doi.org/10.1145/2461466.2461482 [details]
- Kordumova, S., Li, X., & Snoek, C. G. M. (2013). Evaluating Sources and Strategies for Learning Video Concepts from Social Media. In International Workshop on Content-Based Multimedia Indexing http://www.science.uva.nl/research/publications/2013/KordumovaIWCMI2013
- Li, X., & Snoek, C. G. M. (2013). Classifying Tag Relevance with Relevant Positive and Negative Examples. In MM '13: proceedings of the 2013 ACM Multimedia Conference : October 21-25, 2013, Barcelona, Spain (Vol. 2, pp. 485-488). ACM. https://doi.org/10.1145/2502081.2502129 [details]
- Li, X., Snoek, C. G. M., Worring, M., Koelma, D., & Smeulders, A. W. M. (2013). Bootstrapping Visual Categorization with Relevant Negatives. IEEE Transactions on Multimedia, 15(4), 933-945. Advance online publication. https://doi.org/10.1109/TMM.2013.2238523 [details]
- Li, Z., Gavves, E., van de Sande, K. E. A., Snoek, C. G. M., & Smeulders, A. W. M. (2013). Codemaps: Segment, Classify and Search Objects Locally. In 2013 IEEE International Conference on Computer Vision: ICCV 2013 : proceedings: 1-8 December 2013, Sydney, NSW, Australia (pp. 2136-2143). IEEE Computer Society. https://doi.org/10.1109/ICCV.2013.454 [details]
- Mazloom, M., Gavves, E., van de Sande, K. E. A., & Snoek, C. G. M. (2013). Searching Informative Concept Banks for Video Event Detection. In ICMR'13: proceedings of the third ACM International Conference on Multimedia Retrieval : April 16-20, 2013, Dallas, Texas, USA (pp. 255-262). Association for Computing Machinery. https://doi.org/10.1145/2461466.2461507 [details]
- Mazloom, M., Habibian, A., & Snoek, C. G. M. (2013). Querying for Video Events by Semantic Signatures from Few Examples. In MM '13: proceedings of the 2013 ACM Multimedia Conference : October 21-25, 2013, Barcelona, Spain (Vol. 2, pp. 609-612). ACM. https://doi.org/10.1145/2502081.2502160 [details]
- Modolo, D., & Snoek, C. G. M. (2013). Can Object Detectors Aid Internet Video Event Retrieval? In IS\&T/SPIE Symposium on Electronic Imaging http://www.science.uva.nl/research/publications/2013/ModoloSEI2013
2012
- Gavves, E., Snoek, C. G. M., & Smeulders, A. W. M. (2012). Convex reduction of high-dimensional kernels for visual classification. In IEEE Conference on Computer Vision and Pattern Recognition (pp. 3610-3617). IEEE. https://doi.org/10.1109/CVPR.2012.6248106 [details]
- Gavves, E., Snoek, C. G. M., & Smeulders, A. W. M. (2012). Visual synonyms for landmark image retrieval. Computer Vision and Image Understanding, 116(2), 238-249. https://doi.org/10.1016/j.cviu.2011.10.004 [details]
- Huurnink, B., Snoek, C. G. M., de Rijke, M., & Smeulders, A. W. M. (2012). Content-based analysis improves audiovisual archive retrieval. IEEE Transactions on Multimedia, 14(4), 1166-1178. https://doi.org/10.1109/TMM.2012.2193561 [details]
- Li, X., Snoek, C. G. M., Worring, M., & Smeulders, A. W. M. (2012). Fusing concept detection and geo context for visual search. In H. S. I. Horace (Ed.), Proceedings of the 2nd ACM International Conference on Multimedia Retrieval (pp. 4). ACM. https://doi.org/10.1145/2324796.2324801 [details]
- Li, X., Snoek, C. G. M., Worring, M., & Smeulders, A. W. M. (2012). Harvesting social images for bi-concept search. IEEE Transactions on Multimedia, 14(4), 1091-1104. https://doi.org/10.1109/TMM.2012.2191943 [details]
- Vreeswijk, D. T. J., Snoek, C. G. M., van de Sande, K. E. A., & Smeulders, A. W. M. (2012). All vehicles are cars: subclass preferences in container concepts. In H. S. I. Horace (Ed.), ICMR '12: Proceedings of the 2nd ACM International Conference on Multimedia Retrieval (pp. 8). ACM. https://doi.org/10.1145/2324796.2324806 [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2012). Accelerating Visual Categorization with the GPU. In K. N. Kutulakos (Ed.), Trends and Topics in Computer Vision: ECCV 2010 workshops, Heraklion, Crete, Greece, September 10-11, 2010: revised selected papers (Vol. 2, pp. 436-449). (Lecture Notes in Computer Science; Vol. 6554). Springer. https://doi.org/10.1007/978-3-642-35740-4_34 [details]
2011
- Freiburg, B., Kamps, J., & Snoek, C. G. M. (2011). Crowdsourcing visual detectors for video search. In MM '11: proceedings of the 2011 ACM Multimedia Conference & Co-Located Workshops: Nov. 28-Dec. 1, 2011, Scottsdale, AZ, USA (pp. 913-916). Association for Computing Machinery. https://doi.org/10.1145/2072298.2071901 [details]
- Hürst, W., Snoek, C. G. M., Spoel, W-J., & Tomin, M. (2011). Size matters! How thumbnail number, size, and motion influence mobile video retrieval. In K-T. Lee, W-H. Tsai, H-YM. Liao, T. Chen, J-W. Hsieh, & C-C. Tseng (Eds.), Advances in Multimedia Modeling: 17th International Multimedia Modeling Conference, MMM 2011, Taipei, Taiwan, January 5-7, 2011 : proceedings (Vol. 2, pp. 230-240). (Lecture Notes in Computer Science; Vol. 6524). Springer. https://doi.org/10.1007/978-3-642-17829-0_22 [details]
- Li, X., Gavves, E., Snoek, C. G. M., Worring, M., & Smeulders, A. W. M. (2011). Personalizing automated image annotation using cross-entropy. In MM '11: proceedings of the 2011 ACM Multimedia Conference & Co-Located Workshops: Nov. 28-Dec. 1, 2011, Scottsdale, AZ, USA (pp. 233-242). Association for Computing Machinery. https://doi.org/10.1145/2072298.2072330 [details]
- Li, X., Snoek, C. G. M., Worring, M., & Smeulders, A. W. M. (2011). Social negative bootstrapping for visual categorization. In Proceedings of the 1st ACM International Conference on Multimedia Retrieval: ICMR '11 (pp. 12). ACM. https://doi.org/10.1145/1991996.1992008 [details]
- Snoek, C. G. M., & Slaney, M. (2011). Academia meets industry at the Multimedia Grand Challenge. IEEE Multimedia, 18(1), 4-7. https://doi.org/10.1109/MMUL.2011.3 [details]
- Steggink, J., & Snoek, C. G. M. (2011). Adding semantics to image-region annotations with the Name-It-Game. Multimedia Systems, 17(5), 367-378. https://doi.org/10.1007/s00530-010-0220-y [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2011). Empowering Visual Categorization with the GPU. IEEE Transactions on Multimedia, 13(1), 60-70. https://doi.org/10.1109/TMM.2010.2091400 [details]
2010
- Byrne, D., Doherty, A. R., Snoek, C. G. M., Jones, G. J. F., & Smeaton, A. F. (2010). Everyday Concept Detection in Visual Lifelogs: Validation, Relationships and Trends. Multimedia Tools and Applications, 49(1), 119-144. https://doi.org/10.1007/s11042-009-0403-8 [details]
- Gavves, E., & Snoek, C. G. M. (2010). Landmark Image Retrieval Using Visual Synonyms. In MM '10: proceedings of the ACM Multimedia 2010 International Conference: October 25-29, 2010, Firenze, Italy (pp. 1123-1126). Association for Computing Machinery. https://doi.org/10.1145/1873951.1874166 [details]
- Huurnink, B., Snoek, C. G. M., de Rijke, M., & Smeulders, A. W. M. (2010). Today's and tomorrow's retrieval practice in the audiovisual archive. In CIVR 2010: 2010 ACM International Conference on Image and Video Retrieval, at Xi'an, China, July 5-7, 2010 (pp. 18-25). Association for Computing Machinery. https://doi.org/10.1145/1816041.1816045 [details]
- Hürst, W., Snoek, C. G. M., Spoel, W. J., & Tomin, M. (2010). Keep Moving! Revisiting Thumbnails for Mobile Video Retrieval. In MM '10: proceedings of the ACM Multimedia 2010 International Conference: October 25-29, 2010, Firenze, Italy (pp. 963-966). Association for Computing Machinery. https://doi.org/10.1145/1873951.1874124 [details]
- Li, X., Snoek, C. G. M., & Worring, M. (2010). Unsupervised Multi-Feature Tag Relevance Learning for Social Image Retrieval. In CIVR 2010: 2010 ACM International Conference on Image and Video Retrieval, at Xi'an, China, July 5-7, 2010 (pp. 10-17). Association for Computing Machinery. https://doi.org/10.1145/1816041.1816044 [details]
- Snoek, C. G. M., & Smeulders, A. W. M. (2010). Visual-Concept Search Solved? Computer, 43(6), 76-78. https://doi.org/10.1109/MC.2010.183 [details]
- Snoek, C. G. M., Freiburg, B., Oomen, J., & Ordelman, R. (2010). Crowdsourcing Rock N' Roll Multimedia Retrieval. In MM '10: proceedings of the ACM Multimedia 2010 International Conference: October 25-29, 2010, Firenze, Italy (pp. 1535-1538). Association for Computing Machinery. https://doi.org/10.1145/1873951.1874278 [details]
- Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., Gavves, E., Odijk, D., de Rijke, M., Gevers, T., Worring, M., Koelma, D. C., & Smeulders, A. W. M. (2010). The MediaMill TRECVID 2010 semantic video search engine. In TRECVID 2010 notebook National Institute of Standards and Technology. http://www-nlpir.nist.gov/projects/tvpubs/tv10.papers/mediamill.pdf [details]
- van Gemert, J. C., Snoek, C. G. M., Veenman, C. J., Smeulders, A. W. M., & Geusebroek, J. M. (2010). Comparing Compact Codebooks for Visual Categorization. Computer Vision and Image Understanding, 114(4), 450-462. https://doi.org/10.1016/j.cviu.2009.08.004 [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2010). Evaluating Color Descriptors for Object and Scene Recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32(9), 1582-1596. https://doi.org/10.1109/TPAMI.2009.154 [details]
2009
- Li, X., & Snoek, C. G. M. (2009). Visual categorization with negative examples for free. In Proceedings of the 2009 ACM Multimedia Conference & co-located workshops: October 19-24, 2009, Beijing, China (pp. 661-664). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1631272.1631382 [details]
- Li, X., Snoek, C. G. M., & Worring, M. (2009). Annotating images by harnessing worldwide user-tagged photos. In 2009 IEEE International Conference on Acoustics, Speech, and Signal Processing: Proceedings: April 19—24, 2009, Taipei International Convention Center, Taipei, Taiwan (pp. 3717-3720). IEEE. https://doi.org/10.1109/ICASSP.2009.4960434 [details]
- Li, X., Snoek, C. G. M., & Worring, M. (2009). Learning social tag relevance by neighbor voting. IEEE Transactions on Multimedia, 11(7), 1310-1322. https://doi.org/10.1109/TMM.2009.2030598 [details]
- Setz, A. T., & Snoek, C. G. M. (2009). Can social tagged images aid concept-based video search? In 2009 IEEE International Conference on Multimedia and Expo, ICME 2009: Proceedings: June 28-July 3, 2009, Waldorf-Astoria Hotel, New York, New York, U.S.A. (pp. 1460-1463). IEEE. https://doi.org/10.1109/ICME.2009.5202778 [details]
- Snoek, C. G. M., & Worring, M. (2009). Concept-based video retrieval. Foundations and Trends in Information Retrieval, 2(4), 215-322. https://doi.org/10.1561/1500000014 [details]
- Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., Uijlings, J. R. R., van Liempt, M., Bugalho, M., Trancoso, I., Yan, F., Tahir, M. A., Mikolajczyk, K., Kittler, J., de Rijke, M., Geusebroek, J. M., Gevers, T., Worring, M., Smeulders, A. W. M., & Koelma, D. C. (2009). The MediaMill TRECVID 2009 semantic video search engine. In TRECVID 2009 Overview Papers and Slides National Institute of Standards and Technology (NIST). http://www-nlpir.nist.gov/projects/tvpubs/tv9.papers/mediamill.pdf [details]
2008
- Byrne, D., Doherty, A. R., Snoek, C. G. M., Jones, G. G. F., & Smeaton, A. F. (2008). Validating the detection of everyday concepts in visual lifelogs. In D. Duke, L. Hardman, A. Hauptmann, D. Paulus, & S. Staab (Eds.), Semantic Multimedia: Third International Conference on Semantic and Digital Media Technologies, SAMT 2008, Koblenz, Germany, December 3-5, 2008 : proceedings (pp. 15-30). (Lecture Notes in Computer Science; Vol. 5392). Springer. https://doi.org/10.1007/978-3-540-92235-3_4 [details]
- Li, X., Snoek, C. G. M., & Worring, M. (2008). Learning tag relevance by neighbor voting for social image retrieval. In Proceedings of the 1st ACM International Conference on Multimedia Information Retrieval (MIR 2008) (pp. 180-187). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1460096.1460126 [details]
- Snoek, C. G. M., Worring, M., de Rooij, O., van de Sande, K. E. A., Yan, R., & Hauptmann, A. G. (2008). VideOlympics: Real-time evaluation of multimedia retrieval systems. IEEE Multimedia, 15(1), 86-91. https://doi.org/10.1109/MMUL.2008.21 [details]
- Snoek, C. G. M., van Balen, R., Koelma, D. C., Smeulders, A. W. M., & Worring, M. (2008). Analyzing video concept detectors visually. In 2008 IEEE International Conference on Multimedia and Expo: ICME 2008: Proceedings: June 23-26, 2008, Hannover Congress Centrum, Hannover, Germany (pp. 1603-1604). IEEE. https://doi.org/10.1109/ICME.2008.4607759 [details]
- Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., van Gemert, J. C., Uijlings, J. R. R., He, J., Li, X., Everts, I., Nedovic, V., van Liempt, M., van Balen, R., Yan, F., Tahir, M. A., Mikolajczyk, K., Kittler, J., de Rijke, M., Geusebroek, J. M., Gevers, T., ... Koelma, D. C. (2008). The MediaMill TRECVID 2008 semantic video search engine. In TRECVID 2008: Proceedings of the 2008 TREC Video Retrieval Evaluation workshop (pp. 1-14). National Institute of Standards and Technology (NIST). http://www-nlpir.nist.gov/projects/tvpubs/tv8.papers/mediamill.pdf [details]
- de Rooij, O., Snoek, C. G. M., & Worring, M. (2008). Balancing thread based navigation for targeted video search. In CIVR'08: Proceedings of the International Conference on Content-based Image and Video Retrieval, Niagara Falls, Canada, July 7-9, 2008 (pp. 485-494). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1386352.1386414 [details]
- de Rooij, O., Snoek, C. G. M., & Worring, M. (2008). MediaMill: Fast and effective video search using the ForkBrowser. In CIVR'08: Proceedings of the International Conference on Content-based Image and Video Retrieval, Niagara Falls, Canada, July 7-9, 2008 (pp. 561-562). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1386352.1386431 [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2008). A comparison of color features for visual concept classification. In CIVR'08: Proceedings of the International Conference on Content-based Image and Video Retrieval, Niagara Falls, Canada, July 7-9, 2008 (pp. 141-149). Association for Computing Machinery (ACM). http://doi.acm.org/10.1145/1386352.1386376 [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2008). Color descriptors for object category recognition. In CGIV 2008 / MCS'08: 4th European Conference on Colour in Graphics, Imaging, and Vision: 10th International Symposium on Multispectral Colour Science: Final program and proceedings (pp. 378-381). Society for Imaging Science and Technology (IS&T). http://www.imaging.org/store/epub.cfm?abstrid=38777 [details]
- van de Sande, K. E. A., Gevers, T., & Snoek, C. G. M. (2008). Evaluation of color descriptors for object and scene recognition. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition: CVPR 2008 (pp. 1-8). IEEE. https://doi.org/10.1109/CVPR.2008.4587658 [details]
2012
- Cesar, P., Shamma, D. A., Williams, D., & Snoek, C. G. M. (2012). International Workshop on Socially-Aware Multimedia (SAM'12). In MM'12 : the proceedings of the 20th ACM international conference on multimedia, co-located with ACM Multimedia 2012, October 29-November 2, 2012, Nara, Japan (pp. 1503-1504). Association for Computing Machinery. https://doi.org/10.1145/2393347.2396538 [details]
- Xie, L., Shamma, D. A., & Snoek, C. (2012). Content is Dead; Long-Live Content! In MM'12 : the proceedings of the 20th ACM international conference on multimedia, co-located with ACM Multimedia 2012, October 29-November 2, 2012, Nara, Japan (pp. 7). Association for Computing Machinery. https://doi.org/10.1145/2393347.2393355 [details]
2011
- Snoek, C. G. M., & Smeulders, A. W. M. (2011). Internet video search. In MM '11: proceedings of the 2011 ACM Multimedia Conference & Co-Located Workshops: Nov. 28-Dec. 1, 2011, Scottsdale, AZ, USA (pp. 629). Association for Computing Machinery. https://doi.org/10.1145/2072298.2072400 [details]
2009
- Snoek, C. G. M., van de Sande, K. E. A., de Rooij, O., Huurnink, B., Uijlings, J. R. R., van Liempt, M., Bugalho, M., Trancoso, I., Yan, F., Tahir, M. A., Mikolajczyk, K., Kittler, J., de Rijke, M., Geusebroek, J. M., Gevers, T., Worring, M., Smeulders, A. W. M., & Koelma, D. C. (2009). The MediaMill TRECVID 2009 semantic video search engine. In TRECVID 2009 working notes National Institute of Standards and Technology (NIST). http://ilps.science.uva.nl/biblio/mediamill-trecvid-2009-semantic-video-search-engine-draft-notebook-paper [details]
2023
- Najdenkoska, I., Derakhshani, M. M., Snoek, C. G. M., Worring, M., & Asano, Y. M. (2023). Self-Supervised Open-Ended Classification with Small Visual Language Models. https://arxiv.org/pdf/2310.00500.pdf
2016
- Snoek, C. G. M., Dong, J., Li, X., Wei, Q., Wang, X., Lan, W., Gavves, E., Hussein, N., Koelma, D. C., & Smeulders, A. W. M. (2016). University of Amsterdam and Renmin University at TRECVID 2016: Searching Video, Detecting Events and Describing Video. Paper presented at TRECVID workshop 2016, Gaithersburg, Maryland, United States. https://www-nlpir.nist.gov/projects/tvpubs/tv16.papers/mediamill.pdf [details]
2013
- Snoek, C. G. M., van de Sande, K. E. A., Fontijne, D., Habibian, A., Jain, M., Kordumova, S., Li, Z., Mazloom, M., Pintea, S. L., Tao, R., Koelma, D. C., & Smeulders, A. W. M. (2013). MediaMill at TRECVID 2013: Searching Concepts, Objects, Instances and Events in Video. Paper presented at TRECVID 2013 Workshop, Gaithersburg, Maryland, United States. https://www-nlpir.nist.gov/projects/tvpubs/tv13.papers/mediamill.pdf [details]
2012
- Snoek, C. G. M., van de Sande, K. E. A., Habibian, A., Kordumova, S., Li, Z., Mazloom, M., Pintea, S. L., Tao, R., Koelma, D. C., & Smeulders, A. W. M. (2012). The MediaMill TRECVID 2012 semantic video search engine. Paper presented at TRECVID 2012. http://www-nlpir.nist.gov/projects/tvpubs/tv12.papers/mediamill.pdf [details]
2011
- Snoek, C. G. M., van de Sande, K. E. A., Li, X., Mazloom, M., Jiang, Y.-G., Koelma, D. C., & Smeulders, A. W. M. (2011). The MediaMill TRECVID 2011 semantic video search engine. Paper presented at TRECVID 2011 Workshop, Gaithersburg, Maryland, United States. https://www-nlpir.nist.gov/projects/tvpubs/tv11.papers/mediamill.pdf [details]
Prijs / subsidie
- Snoek, C., Mettes, P., Janssen, H., Blanke, T., Groen, I. & Rudinac, S. (2023). Artificial Intelligence for video from a multidisciplinary perspective. https://dsc.uva.nl/programmes/interdisciplinary-phd-programme/hava-lab/hava-lab.html
- Li, X. & Snoek, C. (2016). ACM Multimedia Grand Challenge Award.
- Kordumova, S., Mensink, T. & Snoek, C. G. M. (2016). ICMR Best Paper Prize.
- Habibian, A., Mensink, T. & Snoek, C. G. M. (2014). ACM Multimedia Best Paper Prize.
- Li, X., Snoek, C. & Worring, M. (2010). ACM CIVR Best paper award.
Tijdschriftredactie
- Snoek, C. (member of editorial board) (2020-2022). IEEE Transactions on Pattern Analysis and Machine Intelligence (Journal).
- Snoek, C. (member of editorial board) (2020-2023). Computer Vision and Image Understanding (Journal).
- Snoek, C. (member of editorial board) (2016-2019). ACM Transactions on Multimedia Computing Communications and Applications (Journal).
- Snoek, C. (member of editorial board) (2016). ACM Transactions on Multimedia Computing Communications and Applications (Journal).
- Snoek, C. (member of editorial board) (2016). IEEE Multimedia (Journal).
- Snoek, C. (member of editorial board) (2015). IEEE Transactions on Multimedia (Journal).
- Snoek, C. (member of editorial board) (2015). IEEE Multimedia (Journal).
- Snoek, C. (member of editorial board) (2014). IEEE Transactions on Multimedia (Journal).
- Snoek, C. (member of editorial board) (2014). IEEE Multimedia (Journal).
- Snoek, C. (member of editorial board) (2013). IEEE Multimedia (Journal).
- Snoek, C. (member of editorial board) (2013). IEEE Transactions on Multimedia (Journal).
2017
- Li, Z. (2017). Exploring locality for visual recognition. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
- Mettes, P. S. M. (2017). Objects for spatio-temporal activity recognition in videos. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
- Pintea, S. L. (2017). Continuous learning in computer vision. [Thesis, fully internal, Universiteit van Amsterdam]. [details]
2024
- Zhang, Y., Snoek, C. G. M., Kofinas, M., Knyazev, B., Chen, Y., Burghouts, G. J. & Gavves, S. (8-5-2024). CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks. Zenodo. https://doi.org/10.5281/zenodo.12797219
2022
- Zhang, Y., Doughty, H. R. & Snoek, C. G. M. (19-3-2022). ActorShift.zip. Universiteit van Amsterdam. https://doi.org/10.21942/uva.19387046.v1
2018
- Cappallo, S. H., Svetlichnaya, S., Garrigues, P., Mensink, T. & Snoek, C. (28-2-2018). Twemoji Dataset. Universiteit van Amsterdam. https://doi.org/10.21942/uva.5822100.v3
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Bagad, P., Tapaswi, M., & Snoek, C. G. M. (2023). Test of Time: Instilling Video-Language Models with a Sense of Time. In CVPR 2023: proceedings: 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition : Vancouver, Canada : 18-22 June 2023 (pp. 2503-2516). IEEE Computer Society.