| Social lstm: Human trajectory prediction in crowded spaces A Alahi, K Goel, V Ramanathan, A Robicquet, L Fei-Fei, S Savarese Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 3636 | 2016 |
| Exploring the limits of weakly supervised pretraining D Mahajan, R Girshick, V Ramanathan, K He, M Paluri, Y Li, A Bharambe, ... Proceedings of the European conference on computer vision (ECCV), 181-196, 2018 | 1617 | 2018 |
| Detecting events and key actors in multi-person videos V Ramanathan, J Huang, S Abu-El-Haija, A Gorban, K Murphy, L Fei-Fei Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 261 | 2016 |
| Socially-aware large-scale crowd forecasting A Alahi, V Ramanathan, L Fei-Fei Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 259 | 2014 |
| Shifting weights: Adapting object detectors from image to video K Tang, V Ramanathan, L Fei-Fei, D Koller Advances in neural information processing systems 25, 2012 | 238 | 2012 |
| The llama 3 herd of models A Dubey, A Jauhri, A Pandey, A Kadian, A Al-Dahle, A Letman, A Mathur, ... arXiv preprint arXiv:2407.21783, 2024 | 221 | 2024 |
| What makes a video a video: Analyzing temporal information in video understanding models and datasets DA Huang, V Ramanathan, D Mahajan, L Torresani, M Paluri, L Fei-Fei, ... Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2018 | 160 | 2018 |
| Linking people in videos with “their” names using coreference resolution V Ramanathan, A Joulin, P Liang, L Fei-Fei Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 144 | 2014 |
| Learning semantic relationships for better action retrieval in images V Ramanathan, C Li, J Deng, W Han, Z Li, K Gu, Y Song, S Bengio, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 143 | 2015 |
| Social role discovery in human events V Ramanathan, B Yao, L Fei-Fei Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 143 | 2013 |
| Fast non-local means (NLM) computation with probabilistic early termination R Vignesh, BT Oh, CCJ Kuo IEEE Signal Processing Letters 17 (3), 277-280, 2009 | 124 | 2009 |
| Learning temporal embeddings for complex video analysis V Ramanathan, K Tang, G Mori, L Fei-Fei Proceedings of the IEEE international conference on computer vision, 4471-4479, 2015 | 96 | 2015 |
| Emu: Enhancing image generation models using photogenic needles in a haystack X Dai, J Hou, CY Ma, S Tsai, J Wang, R Wang, P Zhang, S Vandenhende, ... arXiv preprint arXiv:2309.15807, 2023 | 95 | 2023 |
| Adaptive methods for real-world domain generalization A Dubey, V Ramanathan, A Pentland, D Mahajan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 87 | 2021 |
| Video event understanding using natural language descriptions V Ramanathan, P Liang, L Fei-Fei Proceedings of the IEEE international conference on computer vision, 905-912, 2013 | 69 | 2013 |
| Filtering, distillation, and hard negatives for vision-language pre-training F Radenovic, A Dubey, A Kadian, T Mihaylov, S Vandenhende, Y Patel, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2023 | 66 | 2023 |
| Paco: Parts and attributes of common objects V Ramanathan, A Kalia, V Petrovic, Y Wen, B Zheng, B Guo, R Wang, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 63 | 2023 |
| Learning to predict human behavior in crowded scenes A Alahi, V Ramanathan, K Goel, A Robicquet, AA Sadeghian, L Fei-Fei, ... Group and Crowd Behavior for Computer Vision, 183-207, 2017 | 62 | 2017 |
| Activity driven weakly supervised object detection Z Yang, D Mahajan, D Ghadiyaram, R Nevatia, V Ramanathan Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 38 | 2019 |
| Learning to learn from noisy web videos S Yeung, V Ramanathan, O Russakovsky, L Shen, G Mori, L Fei-Fei Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2017 | 35 | 2017 |
Li Fei-FeiProfessor of Computer Science, Stanford UniversityПотвърден имейл адрес: cs.stanford.edu
