| Microsoft coco: Common objects in context TY Lin, M Maire, S Belongie, J Hays, P Perona, D Ramanan, P Dollár, ... Computer Vision–ECCV 2014: 13th European Conference, Zurich, Switzerland …, 2014 | 35847 | 2014 |
| Object detection with discriminatively trained part-based models PF Felzenszwalb, RB Girshick, D McAllester, D Ramanan IEEE transactions on pattern analysis and machine intelligence 32 (9), 1627-1645, 2009 | 12359 | 2009 |
| A discriminatively trained, multiscale, deformable part model P Felzenszwalb, D McAllester, D Ramanan 2008 IEEE conference on computer vision and pattern recognition, 1-8, 2008 | 3657 | 2008 |
| Face detection, pose estimation, and landmark localization in the wild X Zhu, D Ramanan 2012 IEEE conference on computer vision and pattern recognition, 2879-2886, 2012 | 2914 | 2012 |
| Articulated Human Detection with Flexible Mixtures-of-Parts Y Yang, D Ramanan Pattern Analysis and Machine Intelligence, IEEE Transactions on 35 (12 …, 2013 | 2317* | 2013 |
| Globally-optimal greedy algorithms for tracking a variable number of objects H Pirsiavash, D Ramanan, CC Fowlkes CVPR 2011, 1201-1208, 2011 | 1009 | 2011 |
| Argoverse: 3d tracking and forecasting with rich maps MF Chang, J Lambert, P Sangkloy, J Singh, S Bak, A Hartnett, D Wang, ... Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 869 | 2019 |
| Detecting activities of daily living in first-person camera views H Pirsiavash, D Ramanan 2012 IEEE conference on computer vision and pattern recognition, 2847-2854, 2012 | 865 | 2012 |
| Finding tiny faces P Hu, D Ramanan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 859 | 2017 |
| A large-scale benchmark dataset for event recognition in surveillance video S Oh, A Hoogs, A Perera, N Cuntoor, CC Chen, JT Lee, S Mukherjee, ... CVPR 2011, 3153-3160, 2011 | 836 | 2011 |
| Efficiently scaling up crowdsourced video annotation: A set of best practices for high quality, economical video labeling C Vondrick, D Patterson, D Ramanan International journal of computer vision 101, 184-204, 2013 | 764* | 2013 |
| Learning to parse images of articulated bodies D Ramanan Advances in Neural Information Processing Systems 19, 1129, 2007 | 659* | 2007 |
| Discriminative models for multi-class object layout C Desai, D Ramanan, CC Fowlkes International journal of computer vision 95, 1-12, 2011 | 647 | 2011 |
| 3d human pose estimation= 2d pose estimation+ matching CH Chen, D Ramanan Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 574 | 2017 |
| Tracking people by learning their appearance D Ramanan, DA Forsyth, A Zisserman IEEE transactions on pattern analysis and machine intelligence 29 (1), 65-81, 2006 | 518 | 2006 |
| Learning to model the tail YX Wang, D Ramanan, M Hebert Advances in neural information processing systems 30, 2017 | 517 | 2017 |
| Actionvlad: Learning spatio-temporal aggregation for action classification R Girdhar, D Ramanan, A Gupta, J Sivic, B Russell Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 500 | 2017 |
| Look and think twice: Capturing top-down visual attention with feedback convolutional neural networks C Cao, X Liu, Y Yang, Y Yu, J Wang, Z Wang, Y Huang, L Wang, C Huang, ... Proceedings of the IEEE international conference on computer vision, 2956-2964, 2015 | 460 | 2015 |
| Strike a pose: Tracking people by finding stylized poses D Ramanan, DA Forsyth, A Zisserman 2005 IEEE Computer Society Conference on Computer Vision and Pattern …, 2005 | 457 | 2005 |
| Do we need more training data? X Zhu, C Vondrick, CC Fowlkes, D Ramanan International Journal of Computer Vision 119 (1), 76-92, 2016 | 439* | 2016 |
James HaysGeorgia TechVerified email at gatech.edu
