| Learning to predict 3d objects with an interpolation-based differentiable renderer W Chen, H Ling, J Gao, E Smith, J Lehtinen, A Jacobson, S Fidler Advances in neural information processing systems 32, 2019 | 437 | 2019 |
| Improved adversarial systems for 3d object generation and reconstruction EJ Smith, D Meger Conference on Robot Learning, 87-96, 2017 | 215 | 2017 |
| Frame averaging for invariant and equivariant network design O Puny, M Atzmon, H Ben-Hamu, I Misra, A Grover, EJ Smith, Y Lipman arXiv preprint arXiv:2110.03336, 2021 | 129 | 2021 |
| Geometrics: Exploiting geometric structure for graph-encoded objects EJ Smith, S Fujimoto, A Romero, D Meger arXiv preprint arXiv:1901.11461, 2019 | 113 | 2019 |
| Kaolin: A pytorch library for accelerating 3d deep learning research KM Jatavallabhula, E Smith, JF Lafleche, CF Tsang, A Rozantsev, ... arXiv preprint arXiv:1911.05063, 2019 | 92* | 2019 |
| 3d shape reconstruction from vision and touch E Smith, R Calandra, A Romero, G Gkioxari, D Meger, J Malik, M Drozdzal Advances in Neural Information Processing Systems 33, 14193-14206, 2020 | 63 | 2020 |
| Multi-view silhouette and depth decomposition for high resolution 3d object representation E Smith, S Fujimoto, D Meger Advances in Neural Information Processing Systems 31, 2018 | 59 | 2018 |
| For sale: State-action representation learning for deep reinforcement learning S Fujimoto, WD Chang, E Smith, SS Gu, D Precup, D Meger Advances in Neural Information Processing Systems 36, 2024 | 55 | 2024 |
| Active 3D shape reconstruction from vision and touch E Smith, D Meger, L Pineda, R Calandra, J Malik, A Romero Soriano, ... Advances in Neural Information Processing Systems 34, 16064-16078, 2021 | 44 | 2021 |
| Gavriel State, Jason Gorski, Tommy Xiang, Jianing Li, Michael Li, and Rev Lebaredian. Kaolin: A pytorch library for accelerating 3d deep learning research CF Tsang, M Shugrina, JF Lafleche, T Takikawa, J Wang, C Loop, ... | 34 | 2022 |
| Uncertainty-Driven Active Vision for Implicit Scene Reconstruction EJ Smith, M Drozdzal, D Nowrouzezahrai, D Meger, A Romero-Soriano arXiv preprint arXiv:2210.00978, 2022 | 7 | 2022 |
| Deep 3D Shape Understanding EJ Smith McGill University (Canada), 2024 | | 2024 |
| Supplementary of Learning to Predict 3D Objects with an Interpolation-based Differentiable Renderer W Chen, J Gao, H Ling, EJ Smith, J Lehtinen, A Jacobson, S Fidler | | |
David MegerAssociate Professor at McGill Universitycim.mcgill.ca의 이메일 확인됨