| Object tracking: A survey A Yilmaz, O Javed, M Shah Acm computing surveys (CSUR) 38 (4), 13-es, 2006 | 7580 | 2006 |
| UCF101: A dataset of 101 human actions classes from videos in the wild K Soomro, AR Zamir, M Shah arXiv preprint arXiv:1212.0402, 2012 | 6861 | 2012 |
| Transformers in vision: A survey S Khan, M Naseer, M Hayat, SW Zamir, FS Khan, M Shah ACM computing surveys (CSUR) 54 (10s), 1-41, 2022 | 3065 | 2022 |
| Shape-from-shading: a survey R Zhang, PS Tsai, JE Cryer, M Shah IEEE transactions on pattern analysis and machine intelligence 21 (8), 690-706, 1999 | 2314 | 1999 |
| Abnormal crowd behavior detection using social force model R Mehran, A Oyama, M Shah 2009 IEEE conference on computer vision and pattern recognition, 935-942, 2009 | 2301 | 2009 |
| A 3-dimensional sift descriptor and its application to action recognition P Scovanner, S Ali, M Shah Proceedings of the 15th ACM international conference on Multimedia, 357-360, 2007 | 2220 | 2007 |
| Real-world anomaly detection in surveillance videos W Sultani, C Chen, M Shah Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 2109 | 2018 |
| Visual tracking: An experimental survey AWM Smeulders, DM Chu, R Cucchiara, S Calderara, A Dehghan, ... IEEE transactions on pattern analysis and machine intelligence 36 (7), 1442-1468, 2013 | 2061 | 2013 |
| A fast algorithm for active contours and curvature estimation DJ Williams, M Shah CVGIP: Image understanding 55 (1), 14-26, 1992 | 1966 | 1992 |
| Action MACH a spatio-temporal Maximum Average Correlation Height filter for action recognition. MD Rodriguez, J Ahmed, M Shah CVPR 1 (1), 6, 2008 | 1663 | 2008 |
| Action MACH: a spatio-temporal maximum average correlation height filter for action recognition MS Mikel Rodriguez, Ahmed Javed Computer Vision and Pattern Recognition, 2008. CVPR 2008. IEEE Conference on …, 2008 | 1663* | 2008 |
| Recognizing realistic actions from videos “in the wild” J Liu, J Luo, M Shah 2009 IEEE conference on computer vision and pattern recognition, 1996-2003, 2009 | 1555 | 2009 |
| Diffusion models in vision: A survey FA Croitoru, V Hondru, RT Ionescu, M Shah IEEE Transactions on Pattern Analysis and Machine Intelligence 45 (9), 10850 …, 2023 | 1418 | 2023 |
| Visual attention detection in video sequences using spatiotemporal cues Y Zhai, M Shah Proceedings of the 14th ACM international conference on Multimedia, 815-824, 2006 | 1298 | 2006 |
| Multi-source multi-scale counting in extremely dense crowd images H Idrees, I Saleemi, C Seibert, M Shah Proceedings of the IEEE conference on computer vision and pattern …, 2013 | 1226 | 2013 |
| 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 | 1006 | 2011 |
| Composition loss for counting, density map estimation and localization in dense crowds H Idrees, M Tayyab, K Athrey, D Zhang, S Al-Maadeed, N Rajpoot, ... Proceedings of the European conference on computer vision (ECCV), 532-546, 2018 | 902 | 2018 |
| Bayesian modeling of dynamic scenes for object detection Y Sheikh, M Shah IEEE transactions on pattern analysis and machine intelligence 27 (11), 1778 …, 2005 | 880 | 2005 |
| Recognizing 50 human action categories of web videos KK Reddy, M Shah Machine vision and applications 24 (5), 971-981, 2013 | 827 | 2013 |
| A lagrangian particle dynamics approach for crowd flow segmentation and stability analysis S Ali, M Shah 2007 IEEE conference on computer vision and pattern recognition, 1-6, 2007 | 797 | 2007 |
niels loboAssociate Professor of Computer Sciencecs.ucf.edu의 이메일 확인됨
