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Results: 73
Number of items: 73
  • Open Access
    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
  • Open Access
    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
  • Open Access
    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. https://doi.org/10.1145/3377875
  • Open Access
    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 (Vol. 2, 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
  • Open Access
    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
  • 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
  • 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). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00248
  • 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). IEEE Computer Society. https://doi.org/10.1109/ICCVW.2019.00169
  • Ibrahimi, S., Chen, S., Arya, D., Câmara, A., Chen, Y., Crijns, T., van der Goes, M., Mensink, T., van Miltenburg, E., Odijk, D., Thong, W., Zhao, J., & 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). Association for Computing Machinery. https://doi.org/10.1145/3343031.3350597
  • Open Access
    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
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