| No fuss distance metric learning using proxies Y Movshovitz-Attias, A Toshev, TK Leung, S Ioffe, S Singh Proceedings of the IEEE international conference on computer vision, 360-368, 2017 | 739 | 2017 |
| Analysis of the Reputation System and User Contributions on a Question Answering Website: StackOverflow D Movshovitz-Attias, Y Movshovitz-Attias, P Steenkiste, C Faloutsos ASONAM 2013, 2013 | 222 | 2013 |
| Synthetic depth-of-field with a single-camera mobile phone N Wadhwa, R Garg, DE Jacobs, BE Feldman, N Kanazawa, R Carroll, ... ACM Transactions on Graphics (ToG) 37 (4), 1-13, 2018 | 183 | 2018 |
| How useful is photo-realistic rendering for visual learning? Y Movshovitz-Attias, T Kanade, Y Sheikh Computer Vision–ECCV 2016 Workshops: Amsterdam, The Netherlands, October 8 …, 2016 | 154 | 2016 |
| Ontological supervision for fine grained classification of street view storefronts Y Movshovitz-Attias, Q Yu, MC Stumpe, V Shet, S Arnoud, L Yatziv Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 92 | 2015 |
| Videopoet: A large language model for zero-shot video generation D Kondratyuk, L Yu, X Gu, J Lezama, J Huang, R Hornung, H Adam, ... arXiv preprint arXiv:2312.14125, 2023 | 59 | 2023 |
| Wisdom of committees: An overlooked approach to faster and more accurate models X Wang, D Kondratyuk, E Christiansen, KM Kitani, Y Alon, E Eban arXiv preprint arXiv:2012.01988, 2020 | 52 | 2020 |
| Systems and Methods for Automatically Classifying Businesses from Images L Yatziv, Y Movshovitz-Attias, Q Yu, MC Stumpe, VD Shet, SC Arnoud US Patent App. 14/885,452, 2017 | 39 | 2017 |
| 3D Pose-by-Detection of Vehicles via Discriminatively Reduced Ensembles of Correlation Filters Y Movshovitz-Attias, VN Boddeti, Z Wei, Y Sheikh BMVC, 2014 | 29 | 2014 |
| Multiple networks are more efficient than one: Fast and accurate models via ensembles and cascades X Wang, D Kondratyuk, KM Kitani, Y Movshovitz-Attias, E Eban arXiv preprint arXiv:2012.01988, 2020 | 20* | 2020 |
| Structured multi-hashing for model compression E Eban, Y Movshovitz-Attias, H Wu, M Sandler, A Poon, Y Idelbayev, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 16 | 2020 |
| Sky optimization: Semantically aware image processing of skies in low-light photography O Liba, L Cai, YT Tsai, E Eban, Y Movshovitz-Attias, Y Pritch, H Chen, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 15 | 2020 |
| Fine-grained stochastic architecture search SR Chaudhuri, E Eban, H Li, M Moroz, Y Movshovitz-Attias arXiv preprint arXiv:2006.09581, 2020 | 14 | 2020 |
| Differentiable jaccard loss approximation for training an artificial neural network Y Movshovitz-Attias, EET Eban US Patent 10,535,141, 2020 | 13 | 2020 |
| Neural network compression Y Alon, E Eban US Patent 11,928,601, 2024 | 12 | 2024 |
| Distance Metric Learning Using Proxies Y Movshovitz-Attias, KH Leung, S Singh, A Toshev, S Ioffe US Patent App. 15/690,426, 2019 | 9 | 2019 |
| Bacteria-Filters: Persistent particle filters for background subtraction Y Movshovitz-Attias, S Peleg 2010 IEEE International Conference on Image Processing, 677-680, 2010 | 5 | 2010 |
| Dataset curation through renders and ontology matching Y Movshovitz-Attias Ph. D. thesis, Carnegie Mellon University, 2015 | 4 | 2015 |
| Distance metric learning using proxies Y Movshovitz-Attias, KH Leung, S Singh, A Toshev, S Ioffe US Patent 10,387,749, 2019 | 3 | 2019 |
| Weight compression for deep networks using Kronecker products Y Movshovitz-Attias, E Eban | 2 | 2018 |
Elad EbanGoogle在 google.com 的电子邮件经过验证
