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Results: 11
Number of items: 11
  • Open Access
    Hu, V. T., Wu, D., Asano, Y. M., Mettes, P., Fernández-Méndez, F., Ommer, B., & Snoek, C. G. M. (2024). Flow Matching for Conditional Text Generation in a Few Sampling Steps. In Y. Graham, & M. Purver (Eds.), The 18th Conference of the European Chapter of the Association for Computational Linguistics: proceedings of the conference : EACL 2024 : March 17-22, 2024 (Vol. 2, pp. 380-392). Association for Computational Linguistics. https://doi.org/10.18653/v1/2024.eacl-short.33
  • Open Access
    Hu, V. T., Zhang, W., Tang, M., Mettes, P., Zhao, D., & Snoek, C. (2024). Latent Space Editing in Transformer-Based Flow Matching. In M. Wooldridge, J. Dy, & S. Natarajan (Eds.), Proceedings of the 38th AAAI Conference on Artificial Intelligence: AAAI-2024 (Vol. 3, pp. 2247-2255). AAAI Press. https://doi.org/10.1609/aaai.v38i3.27998
  • Open Access
    Hu, T., Thong, W., Mettes, P., & Snoek, C. G. M. (2023). Query by Activity Video in the Wild. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2311.13895
  • Open Access
    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
  • Open Access
    Hu, T. (2023). Label-efficient learning to see. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
  • 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
    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
  • Zhang, C., Hu, T., Guan, Y., & Ye, Z. (2019). Accelerating Convolutional Neural Networks with Dynamic Channel Pruning. 563. Abstract from 2019 Data Compression Conference, Snowbird, Utah, United States. https://doi.org/10.1109/DCC.2019.00075
  • Open Access
    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
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