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Results: 10
Number of items: 10
  • Open Access
    Yin, R., Chen, Y., Karaoglu, S., & Gevers, T. (2025). Ray-Distance Volume Rendering for Neural Scene Reconstruction. In A. Leonardis, E. Ricci, S. Roth, O. Russakovsky, T. Sattler, & G. Varol (Eds.), Computer Vision – ECCV 2024: 18th European Conference, Milan, Italy, September 29–October 4, 2024 : proceedings (Vol. XIV, pp. 377–394). (Lecture Notes in Computer Science; Vol. 15072). Springer. https://doi.org/10.1007/978-3-031-72630-9_22
  • Kofinas, M., Knyazev, B., Zhang, Y., Chen, Y., Burghouts, G. J., Gavves, S., Snoek, C. G., & Zhang, D. (2024, May 8). CNN Wild Park - Graph Neural Networks for Learning Equivariant Representations of Neural Networks [Data set]. Zenodo. https://doi.org/10.5281/zenodo.12797219
  • Open Access
    Liu, J., Yin, W., Wang, H., Chen, Y., Sonke, J.-J., & Gavves, E. (2024). Dynamic Prototype Adaptation with Distillation for Few-shot Point Cloud Segmentation. In 2024 International Conference in 3D Vision: 3DV 2024 : 18-21 March 2024, Davos, Switzerland : proceedings (pp. 810-819). IEEE Computer Society. https://doi.org/10.1109/3DV62453.2024.00045
  • Open Access
    Chen, Y. (2023). Continuity in 3D visual learning. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Chen, Y., Fernando, B., Bilen, H., Nießner, M., & Gavves, E. (2022). 3D Equivariant Graph Implicit Functions. 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. III, pp. 485–502). (Lecture Notes in Computer Science; Vol. 13663). Springer. https://doi.org/10.48550/arXiv.2203.17178, https://doi.org/10.1007/978-3-031-20062-5_28
  • Open Access
    Chen, Y., Fernando, B., Bilen, H., Mensink, T., & Gavves, E. (2021). Neural Feature Matching in Implicit 3D Representations. Proceedings of Machine Learning Research, 139, 1582-1593. https://proceedings.mlr.press/v139/chen21f.html
  • Open Access
    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
  • 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
  • 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
    Chen, Y., Mensink, T., & Gavves, E. (2019). 3D Neighborhood Convolution: Learning Depth-Aware Features for RGB-D and RGB Semantic Segmentation. In 2019 International Conference on 3D Vision: 3DV 2019 : proceedings : Quebec, Canada, 15-18 September 2019 (pp. 173-182). IEEE Computer Society, Conference Publishing Services. https://doi.org/10.48550/arXiv.1910.01460, https://doi.org/10.1109/3DV.2019.00028
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