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Results: 73
Number of items: 73
  • Schutte, J., & Mettes, P. (2022). Teaching a New Dog Old Tricks: Contrastive Random Walks in Videos with Unsupervised Priors. In ICMR '22: proceedings of the 2022 International Conference on Multimedia Retrieval : June 27-30, 2022, Newark, NJ, USA (pp. 176-184). The Association for Computing Machinery. https://doi.org/10.1145/3512527.3531376
  • Open Access
    Ülger, O., Wiederer, J., Ghafoorian, M., Belagiannis, V., & Mettes, P. (2022). Multi-Task Edge Prediction in Temporally-Dynamic Video Graphs. In The 33rd British Machine Vision Conference Proceedings: BMVC 2022 : 21st-24th November 2022, London, UK Article 968 BMVA Press. https://bmvc2022.mpi-inf.mpg.de/968/
  • Open Access
    Zhao, J. (2022). Learning continuity for image and video recognition. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    GhadimiAtigh, M., Schoep, J., Acar, E., van Noord, N., & Mettes, P. (2022). Hyperbolic Image Segmentation. In 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition: New Orleans, Louisiana, 19-24 June 2022 : proceedings (pp. 4443-4452). (CVPR). IEEE Computer Society. https://doi.org/10.1109/CVPR52688.2022.00441
  • Open Access
    Shi, Z. (2022). Inductive biases for pixel representation learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    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
  • Open Access
    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
  • Open Access
    Byvshev, P., Mettes, P., & Xiao, Y. (2022). Are 3D convolutional networks inherently biased towards appearance? Computer Vision and Image Understanding, 220, Article 103437. https://doi.org/10.1016/j.cviu.2022.103437
  • Open Access
    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
  • Open Access
    Bretti, C., & Mettes, P. (2021). Zero-Shot Action Recognition from Diverse Object-Scene Compositions. In 32nd British Machine Vision Conference 2021: BMVC 2021, Online, November 22-25, 2021 Article 281 BMVA Press.
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