| Non-local neural networks X Wang, R Girshick, A Gupta, K He Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 7327 | 2018 |
| Unsupervised visual representation learning by context prediction C Doersch, A Gupta, AA Efros Proceedings of the IEEE international conference on computer vision, 1422-1430, 2015 | 2402 | 2015 |
| Training region-based object detectors with online hard example mining A Shrivastava, A Gupta, R Girshick Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 2183 | 2016 |
| The visual object tracking vot2015 challenge results M Kristan, J Matas, A Leonardis, M Felsberg, L Cehovin, G Fernandez, ... Proceedings of the IEEE international conference on computer vision …, 2015 | 1982 | 2015 |
| Revisiting unreasonable effectiveness of data in deep learning era C Sun, A Shrivastava, S Singh, A Gupta Proceedings of the IEEE international conference on computer vision, 843-852, 2017 | 1944 | 2017 |
| Target-driven visual navigation in indoor scenes using deep reinforcement learning Y Zhu, R Mottaghi, E Kolve, JJ Lim, A Gupta, L Fei-Fei, A Farhadi 2017 IEEE international conference on robotics and automation (ICRA), 3357-3364, 2017 | 1426 | 2017 |
| Unsupervised learning of visual representations using videos X Wang, A Gupta Proceedings of the IEEE international conference on computer vision, 2794-2802, 2015 | 1134 | 2015 |
| Ensemble of exemplar-svms for object detection and beyond T Malisiewicz, A Gupta, AA Efros 2011 International conference on computer vision, 89-96, 2011 | 1111 | 2011 |
| Supersizing self-supervision: Learning to grasp from 50k tries and 700 robot hours L Pinto, A Gupta 2016 IEEE international conference on robotics and automation (ICRA), 3406-3413, 2016 | 1090 | 2016 |
| Cross-stitch networks for multi-task learning I Misra, A Shrivastava, A Gupta, M Hebert Proceedings of the IEEE conference on computer vision and pattern …, 2016 | 1064 | 2016 |
| Never-ending learning T Mitchell, W Cohen, E Hruschka, P Talukdar, B Yang, J Betteridge, ... Communications of the ACM 61 (5), 103-115, 2018 | 1059 | 2018 |
| Hollywood in homes: Crowdsourcing data collection for activity understanding GA Sigurdsson, G Varol, X Wang, A Farhadi, I Laptev, A Gupta Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 952 | 2016 |
| What makes paris look like paris? C Doersch, S Singh, A Gupta, J Sivic, A Efros ACM Transactions on Graphics 31 (4), 2012 | 742 | 2012 |
| Unsupervised discovery of mid-level discriminative patches S Singh, A Gupta, AA Efros Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 730 | 2012 |
| Videos as space-time region graphs X Wang, A Gupta Proceedings of the European conference on computer vision (ECCV), 399-417, 2018 | 676 | 2018 |
| Learning a predictable and generative vector representation for objects R Girdhar, DF Fouhey, M Rodriguez, A Gupta Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 669 | 2016 |
| Robust adversarial reinforcement learning L Pinto, J Davidson, R Sukthankar, A Gupta International Conference on Machine Learning, 2817-2826, 2017 | 662 | 2017 |
| Generative image modeling using style and structure adversarial networks X Wang, A Gupta Computer Vision–ECCV 2016: 14th European Conference, Amsterdam, The …, 2016 | 634 | 2016 |
| Openimages: A public dataset for large-scale multi-label and multi-class image classification I Krasin, T Duerig, N Alldrin, V Ferrari, S Abu-El-Haija, A Kuznetsova, ... Dataset available from https://github. com/openimages 2 (3), 18, 2017 | 618 | 2017 |
| Observing human-object interactions: Using spatial and functional compatibility for recognition A Gupta, A Kembhavi, LS Davis IEEE transactions on pattern analysis and machine intelligence 31 (10), 1775 …, 2009 | 617 | 2009 |
Abhinav ShrivastavaAssistant Professor, University of Maryland, College Park在 cs.umd.edu 的电子邮件经过验证
