| Abc dataset normal estimation benchmark S Koch, A Matveev, Z Jiang, F Williams, A Artemov, E Burnaev, M Alexa, ... | 1 | 2019 |
| Abc: A big cad model dataset for geometric deep learning S Koch, A Matveev, Z Jiang, F Williams, A Artemov, E Burnaev, M Alexa, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 454 | 2019 |
| Approximately Piecewise E (3) Equivariant Point Networks M Atzmon, J Huang, F Williams, O Litany arXiv preprint arXiv:2402.08529, 2024 | | 2024 |
| Deep geometric prior for surface reconstruction F Williams, T Schneider, C Silva, D Zorin, J Bruna, D Panozzo Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 200 | 2019 |
| fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence F Williams, J Huang, J Swartz, G Klár, V Thakkar, M Cong, X Ren, R Li, ... arXiv preprint arXiv:2407.01781, 2024 | | 2024 |
| Generating complete three-dimensional scene geometries using machine learning D Zhang, A Kar, F Williams, Z Gojcic, K Kreis, S Fidler US Patent App. 18/339,936, 2024 | | 2024 |
| Geometric computing with python S Koch, T Schneider, F Williams, D Panozzo ACM SIGGRAPH 2019 Courses, 1-45, 2019 | 9 | 2019 |
| Geometric Priors of Neural Networks F Williams New York University Tandon School of Engineering, 2021 | | 2021 |
| Gradient dynamics of shallow univariate relu networks F Williams, M Trager, D Panozzo, C Silva, D Zorin, J Bruna Advances in neural information processing systems 32, 2019 | 88 | 2019 |
| Human 3D keypoints via spatial uncertainty modeling F Williams, O Litany, A Sud, K Swersky, A Tagliasacchi arXiv preprint arXiv:2012.10518, 2020 | | 2020 |
| Learning smooth neural functions via lipschitz regularization HTD Liu, F Williams, A Jacobson, S Fidler, O Litany ACM SIGGRAPH 2022 Conference Proceedings, 1-13, 2022 | 76 | 2022 |
| Learning to Jointly Understand Visual and Tactile Signals Y Li, Y Du, C Liu, F Williams, M Foshey, B Eckart, J Kautz, JB Tenenbaum, ... The Twelfth International Conference on Learning Representations, 2023 | 1 | 2023 |
| Lion: Latent point diffusion models for 3d shape generation A Vahdat, F Williams, Z Gojcic, O Litany, S Fidler, K Kreis Advances in Neural Information Processing Systems 35, 10021-10039, 2022 | 315 | 2022 |
| NeRF-XL: Scaling NeRFs with Multiple GPUs R Li, S Fidler, A Kanazawa, F Williams arXiv preprint arXiv:2404.16221, 2024 | 1 | 2024 |
| Neural fields as learnable kernels for 3d reconstruction F Williams, Z Gojcic, S Khamis, D Zorin, J Bruna, S Fidler, O Litany Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 51 | 2022 |
| Neural kernel surface reconstruction J Huang, Z Gojcic, M Atzmon, O Litany, S Fidler, F Williams Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 34 | 2023 |
| Neural lidar fields for novel view synthesis S Huang, Z Gojcic, Z Wang, F Williams, Y Kasten, S Fidler, K Schindler, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 28 | 2023 |
| Neural splines: Fitting 3d surfaces with infinitely-wide neural networks F Williams, M Trager, J Bruna, D Zorin Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 57 | 2021 |
| Or Litany, Sanja Fidler, and Karsten Kreis X Zeng, A Vahdat, F Williams, Z Gojcic Lion: Latent point diffusion models for 3d shape generation 4, 2022 | 16 | 2022 |
| Outdoor Scene Extrapolation with Hierarchical Generative Cellular Automata D Zhang, F Williams, Z Gojcic, K Kreis, S Fidler, YM Kim, A Kar Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | | 2024 |
