| Accelerating 3d deep learning with pytorch3d N Ravi, J Reizenstein, D Novotny, T Gordon, WY Lo, J Johnson, ... arXiv preprint arXiv:2007.08501, 2020 | 836 | 2020 |
| Common objects in 3d: Large-scale learning and evaluation of real-life 3d category reconstruction J Reizenstein, R Shapovalov, P Henzler, L Sbordone, P Labatut, ... Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 390 | 2021 |
| isdf: Real-time neural signed distance fields for robot perception J Ortiz, A Clegg, J Dong, E Sucar, D Novotny, M Zollhoefer, M Mukadam arXiv preprint arXiv:2204.02296, 2022 | 139 | 2022 |
| C3dpo: Canonical 3d pose networks for non-rigid structure from motion D Novotny, N Ravi, B Graham, N Neverova, A Vedaldi Proceedings of the IEEE/CVF international conference on computer vision …, 2019 | 126 | 2019 |
| Semi-convolutional operators for instance segmentation D Novotny, S Albanie, D Larlus, A Vedaldi Proceedings of the European Conference on Computer Vision (ECCV), 86-102, 2018 | 110 | 2018 |
| Holodiffusion: Training a 3d diffusion model using 2d images A Karnewar, A Vedaldi, D Novotny, NJ Mitra Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 102 | 2023 |
| Learning 3D Object Categories by Looking Around Them D Novotny, D Larlus, A Vedaldi Proceedings of the IEEE International Conference on Computer Vision, 2017 | 86 | 2017 |
| Self-supervised learning of geometrically stable features through probabilistic introspection D Novotny, S Albanie, D Larlus, A Vedaldi Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 83 | 2018 |
| 3d multi-bodies: Fitting sets of plausible 3d human models to ambiguous image data B Biggs, D Novotny, S Ehrhardt, H Joo, B Graham, A Vedaldi Advances in neural information processing systems 33, 20496-20507, 2020 | 82 | 2020 |
| Continuous surface embeddings N Neverova, D Novotny, M Szafraniec, V Khalidov, P Labatut, A Vedaldi Advances in Neural Information Processing Systems 33, 17258-17270, 2020 | 81 | 2020 |
| AnchorNet: A Weakly Supervised Network to Learn Geometry-sensitive Features For Semantic Matching D Novotny, D Larlus, A Vedaldi Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2017 | 71 | 2017 |
| Unsupervised learning of 3d object categories from videos in the wild P Henzler, J Reizenstein, P Labatut, R Shapovalov, T Ritschel, A Vedaldi, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 68 | 2021 |
| Accelerating 3d deep learning with pytorch3d J Johnson, N Ravi, J Reizenstein, D Novotny, S Tulsiani, C Lassner, ... SIGGRAPH Asia 2020 courses, 1-1, 2020 | 68 | 2020 |
| Neuromorph: Unsupervised shape interpolation and correspondence in one go M Eisenberger, D Novotny, G Kerchenbaum, P Labatut, N Neverova, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 65 | 2021 |
| Posediffusion: Solving pose estimation via diffusion-aided bundle adjustment J Wang, C Rupprecht, D Novotny Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 52 | 2023 |
| Pytorch3d N Ravi, J Reizenstein, D Novotny, T Gordon, WY Lo, J Johnson, ... Pytorch3d, 2020 | 36 | 2020 |
| Correlated uncertainty for learning dense correspondences from noisy labels N Neverova, D Novotny, A Vedaldi Advances in Neural Information Processing Systems 32, 2019 | 31 | 2019 |
| Holofusion: Towards photo-realistic 3d generative modeling A Karnewar, NJ Mitra, A Vedaldi, D Novotny Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 28 | 2023 |
| PerspectiveNet: A Scene-consistent Image Generator for New View Synthesis in Real Indoor Environments D Novotny, B Graham, J Reizenstein Advances in Neural Information Processing Systems, 7599-7610, 2019 | 24 | 2019 |
| I have seen enough: Transferring parts across categories D Novotny, D Larlus, A Vedaldi British Machine Vision Conference, 2016 | 24 | 2016 |