| 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 | 444 | 2021 |
| Non-associative markov networks for 3D point cloud classification R Shapovalov, A Velizhev, O Barinova Photogrammetric Computer Vision and Image Analysis (PCV 2010) 38 (Part 3A …, 2010 | 156 | 2010 |
| Implicit shape models for object detection in 3D point clouds A Velizhev, R Shapovalov, K Schindler ISPRS Congress, 2012 | 88 | 2012 |
| 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 | 74 | 2021 |
| Cutting-plane training of non-associative Markov network for 3D point cloud segmentation R Shapovalov, A Velizhev International Conference on 3D Imaging, Modeling, Processing, Visualization …, 2011 | 50 | 2011 |
| Spatial Inference Machines R Shapovalov, D Vetrov, P Kohli IEEE Conference on Computer Vision and Pattern Recognition, 2013 | 49 | 2013 |
| Novel-view acoustic synthesis C Chen, A Richard, R Shapovalov, VK Ithapu, N Neverova, K Grauman, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 27 | 2023 |
| Common pets in 3d: Dynamic new-view synthesis of real-life deformable categories S Sinha, R Shapovalov, J Reizenstein, I Rocco, N Neverova, A Vedaldi, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 13 | 2023 |
| KeyTr: Keypoint Transporter for 3D Reconstruction of Deformable Objects in Videos D Novotny, I Rocco, S Sinha, A Carlier, G Kerchenbaum, R Shapovalov, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 10 | 2022 |
| Meta 3d assetgen: Text-to-mesh generation with high-quality geometry, texture, and pbr materials Y Siddiqui, T Monnier, F Kokkinos, M Kariya, Y Kleiman, E Garreau, ... arXiv preprint arXiv:2407.02445, 2024 | 9 | 2024 |
| Canonical 3D Deformer Maps: Unifying parametric and non-parametric methods for dense weakly-supervised category reconstruction D Novotny, R Shapovalov, A Vedaldi Advances in Neural Information Processing Systems 33, 2020 | 9 | 2020 |
| Online random forest for interactive image segmentation O Barinova, R Shapovalov, S Sudakov, A Velizhev International Workshop on Experimental Economics and Machine Learning, 2012 | 8 | 2012 |
| Meta 3d gen R Bensadoun, T Monnier, Y Kleiman, F Kokkinos, Y Siddiqui, M Kariya, ... arXiv preprint arXiv:2407.02599, 2024 | 7 | 2024 |
| Efficient road mapping via interactive image segmentation O Barinova, R Shapovalov, S Sudakov, A Velizhev, A Konushin 3D City Models, Road Databases and Traffic Monitoring (CMRT 2009), 1-8, 2009 | 6 | 2009 |
| DensePose 3D: Lifting Canonical Surface Maps of Articulated Objects to the Third Dimension R Shapovalov, D Novotny, B Graham, P Labatut, A Vedaldi Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2021 | 5 | 2021 |
| Replay: Multi-modal Multi-view Acted Videos for Casual Holography R Shapovalov, Y Kleiman, I Rocco, D Novotny, A Vedaldi, C Chen, ... Proceedings of the IEEE/CVF International Conference on Computer Vision …, 2023 | 2 | 2023 |
| Семантическая сегментация данных лазерного сканирования Р Шаповалов, А Велижев, О Баринова, А Конушин Программные продукты и системы, 47-52, 2012 | 1 | 2012 |
| Robust LIDAR data segmentation using compact point clusters AB Velizhev, RV Shapovalov, D Potapov, L Tretiak, A Konushin GraphiCon'2009, 241-244, 2009 | 1 | 2009 |
| UnCommon Objects in 3D X Liu, P Tayal, J Wang, J Zarzar, T Monnier, K Tertikas, J Duan, A Toisoul, ... arXiv preprint arXiv:2501.07574, 2025 | | 2025 |
| GOEmbed: Gradient Origin Embeddings for Representation Agnostic 3D Feature Learning A Karnewar, R Shapovalov, T Monnier, A Vedaldi, NJ Mitra, D Novotny European Conference on Computer Vision, 454-472, 2025 | | 2025 |
David NovotnyFacebook AI ResearchΗ διεύθυνση ηλεκτρονικού ταχυδρομείου έχει επαληθευτεί στον τομέα robots.ox.ac.uk
