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Results: 318
Number of items: 318
  • Open Access
    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
  • Open Access
    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
  • Open Access
    Rastegar, S., Doughty, H., & Snoek, C. G. M. (2023). Learn to Categorize or Categorize to Learn? Self-Coding for Generalized Category Discovery. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (pp. 72794-72818). (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://doi.org/10.52202/075280-3183
  • Open Access
    Du, Y., Xiao, Z., Liao, S., & Snoek, C. G. M. (2023). ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusion. In A. Oh, T. Naumann, A. Globerson, K. Saenko, M. Hardt, & S. Levine (Eds.), 37th Conference on Neural Information Processing Systems (NeurIPS 2023): 10-16 December 2023, New Orleans, Louisana, USA (pp. 46304-46322). (Advances in Neural Information Processing Systems; Vol. 36). Neural Information Processing Systems Foundation. https://doi.org/10.52202/075280-2008
  • Open Access
    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. https://doi.org/10.1177/00491241221099554
  • Open Access
    Chen, S. (2023). Machine perception of interactivity in videos. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
  • Open Access
    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. Proceedings of Machine Learning Research, 202, 32847-32858. https://proceedings.mlr.press/v202/sun23b.html
  • Open Access
    Hu, T. (2023). Label-efficient learning to see. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
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