Dr. P.S.M. (Pascal) Mettes
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Informatics Institute
Bezoekadres
- Science Park 904
- Kamernummer: C3249
Postadres
- Postbus 94323
1090 GH Amsterdam
Contactgegevens
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Publicaties
2023
- Mettes, P. (2023). Hyperbolic Graph Codebooks. In G. Nicosia, V. Ojha, E. La Malfa, G. La Malfa, P. Pardalos, G. Di Fatta, G. Giuffrida, & R. Umeton (Eds.), Machine Learning, Optimization, and Data Science: 8th International Conference, LOD 2022, Certosa di Pontignano, Italy, September 19–22, 2022, Revised Selected Papers (Vol. I, pp. 48-61). (Lecture Notes in Computer Science; Vol. 13810). Springer. https://doi.org/10.1007/978-3-031-25599-1_5 [details]
2022
Byvshev, P., Mettes, P., & Xiao, Y. (2022). Are 3D convolutional networks inherently biased towards appearance? Computer Vision and Image Understanding, 220, [103437]. https://doi.org/10.1016/j.cviu.2022.103437 [details]- Ghadimi Atigh, M., Keller-Ressel, M., & Mettes, P. (2022). Hyperbolic Busemann Learning with Ideal Prototypes. In M. Ranzato, A. Beygelzimer, Y. Dauphin, P. S. Liang, & J. Wortman Vaughan (Eds.), 35th Conference on Neural Information Processing Systems (NeurIPS 2021) : online, 6-14 December 2021 (Vol. 1, pp. 103-115). (Advances in Neural Information Processing Systems; Vol. 34). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2021/hash/01259a0cb2431834302abe2df60a1327-Abstract.html [details]
- Ghadimiatigh, M., Schoep, J., Acar, E., van Noord, N. J. E., & Mettes, P. S. M. (2022). Hyperbolic Image Segmentation. In IEEE Conference on Computer Vision and Pattern Recognition IEEE.
- Kasarla, T., Burghouts, G. J., van Spengler, M. W. F., van der Pol, E. E., Cucchiara, R., & Mettes, P. S. M. (2022). Maximum Class Separation as Inductive Bias in One Matrix. In Advances in Neural Information Processing Systems Neural Information Processing Systems Foundation.
- Schutte, J., & Mettes, P. (2022). Teaching a New Dog Old Tricks: Contrastive Random Walks in Videos with Unsupervised Priors. In International Conference on Multimedia Retrieval ACM. https://doi.org/10.1145/3512527.3531376
- 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. https://doi.org/10.1007/s11263-021-01572-7 [details]
- 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. https://doi.org/10.1007/978-3-031-19830-4_26 [details]
- Ülger, O., Wiederer, J., Ghafoorian, M., Belagiannis, V., & Mettes, P. S. M. (2022). Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs. In British Machine Vision Conference
2021
- Bretti, C., & Mettes, P. S. M. (2021). Zero-Shot Action Recognition from Diverse Object-Scene Compositions. In British Machine Vision Conference
- Chen, S., Mettes, P. S. M., & Snoek, C. G. M. (2021). Diagnosing Errors in Video Relation Detectors. In British Machine Vision Conference
- 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]
- 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. 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. https://doi.org/10.1109/TIP.2021.3106812 [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]
2020
- Byvshev, P., Mettes, P., & Xiao, Y. (2020). Heterogeneous Non-Local Fusion for Multimodal Activity Recognition. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 63-72). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390675 [details]
- 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]
- Dijt, P., & Mettes, P. (2020). Trajectory Prediction Network for Future Anticipation of Ships. In ICMR '20: proceedings of the 2020 International Conference on Multimedia Retrieval : June 08-11, 2020, Dublin, Ireland (pp. 73-81). The Association for Computing Machinery. https://doi.org/10.1145/3372278.3390676 [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), [44]. 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. 1476-1477). (Advances in Neural Information Processing Systems; Vol. 32). Neural Information Processing Systems Foundation. https://papers.nips.cc/paper/2019/hash/02a32ad2669e6fe298e607fe7cc0e1a0-Abstract.html [details]
- Thong, W., Mettes, P., & Snoek, C. G. M. (2020). Open Cross-Domain Visual Search. Computer Vision and Image Understanding, 200, [103045]. 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]
- Zuanazzi, V., van Vugt, J., Booij, O., & Mettes, P. (2020). Adversarial Self-Supervised Scene Flow Estimation. In 2020 International Conference on 3D Vision: 3DV 2020 : proceedings : 25-28 November 2020, virtual event (pp. 1049-1058). IEEE Computer Society. https://doi.org/10.1109/3DV50981.2020.00115 [details]
2019
- Brown, A., Mettes, P., & Worring, M. (2019). 4-Connected Shift Residual Networks. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 1990-1997). Los Alamitos, California: IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00248 [details]
- Hommos, O., Pintea, S. L., Mettes, P. S. M., & van Gemert, J. C. (2019). Using phase instead of optical flow for action recognition. In L. Leal-Taixé, & S. Roth (Eds.), Computer Vision – ECCV 2018 Workshops: Munich, Germany, September 8-14, 2018 : proceedings (Vol. VI, pp. 678-691). (Lecture Notes in Computer Science; Vol. 11134). Springer. https://doi.org/10.1007/978-3-030-11024-6_51 [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]
- Ibrahimi, S., Chen, S., Arya, D., Câmara, A., Chen, Y., Crijns, T., ... Mettes, P. (2019). Interactive Exploration of Journalistic Video Footage through Multimodal Semantic Matching. In MM'19: proceedings of the 27th ACM Conference on Multimedia : October 21-25, 2019, Nice, France (pp. 2196-2198). New York, NY: Association for Computing Machinery. https://doi.org/10.1145/3343031.3350597 [details]
- Mettes, P., & Snoek, C. G. M. (2019). Pointly-Supervised Action Localization. International Journal of Computer Vision, 127(3), 263–281. https://doi.org/10.1007/s11263-018-1120-4 [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]
- de la Riva, M., & Mettes, P. (2019). Bayesian 3D ConvNets for Action Recognition from Few Examples. In 2019 International Conference on Computer Vision, Workshops: proceedings : 27 October-2 November 2019, Seoul, Korea (pp. 1337-1343). Los Alamitos, California: IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00169 [details]
2017
- 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 [22] BMVA Press. https://doi.org/10.5244/C.31.22 [details]
2016
- 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. 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]
2015
- 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]
- 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., Verschoor, C. R., Mettes, P., Epema, K., Koh, L. P., & Wich, S. (2015). Nature Conservation Drones for Automatic Localization and Counting of Animals. In L. Agapito, M. M. Bronstein, & C. Rother (Eds.), Computer Vision - ECCV 2014 Workshops: Zurich, Switzerland, September 6-7 and 12, 2014: proceedings (Vol. 1, pp. 255-270). (Lecture Notes in Computer Science ; Vol. 8925). Springer. https://doi.org/10.1007/978-3-319-16178-5_17 [details]
2014
- Snoek, C. G. M., van de Sande, K. E. A., Fontijne, D., Cappallo, S., van Gemert, J., Habibian, A., ... 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 Gaithersburg, MD: National Institute of Standards and Technology. [details]
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Nevenwerkzaamheden
- Geen nevenwerkzaamheden
Byvshev, P., Mettes, P., & Xiao, Y. (2022). Are 3D convolutional networks inherently biased towards appearance? Computer Vision and Image Understanding, 220, [103437].