| 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 | 2056 | 2013 |
| Gmcp-tracker: Global multi-object tracking using generalized minimum clique graphs A Roshan Zamir, A Dehghan, M Shah Computer Vision–ECCV 2012: 12th European Conference on Computer Vision …, 2012 | 519 | 2012 |
| Part-based multiple-person tracking with partial occlusion handling G Shu, A Dehghan, O Oreifej, E Hand, M Shah 2012 IEEE Conference on Computer Vision and Pattern Recognition, 1815-1821, 2012 | 495 | 2012 |
| GMMCP Tracker: Globally Optimal Generalized Maximum Multi Clique Problem for Multiple Object Tracking A Dehghan, MA Shayan, M Shah CVPR 1, 2, 2015 | 402 | 2015 |
| License plate detection and recognition using deeply learned convolutional neural networks SZ Masood, G Shu, A Dehghan, EG Ortiz arXiv preprint arXiv:1703.07330, 2017 | 195 | 2017 |
| ARKitScenes: A Diverse Real-World Dataset For 3D Indoor Scene Understanding Using Mobile RGB-D Data G Baruch, Z Chen, A Dehghan, T Dimry, Y Feigin, P Fu, T Gebauer, ... arXiv preprint arXiv:2111.08897, 2021 | 188 | 2021 |
| Target identity-aware network flow for online multiple target tracking A Dehghan, Y Tian, PHS Torr, M Shah Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 155 | 2015 |
| Who do i look like? determining parent-offspring resemblance via gated autoencoders A Dehghan, EG Ortiz, R Villegas, M Shah Proceedings of the IEEE conference on computer vision and pattern …, 2014 | 143 | 2014 |
| Dager: Deep age, gender and emotion recognition using convolutional neural network A Dehghan, EG Ortiz, G Shu, SZ Masood arXiv preprint arXiv:1702.04280, 2017 | 141 | 2017 |
| Gaudi: A neural architect for immersive 3d scene generation MA Bautista, P Guo, S Abnar, W Talbott, A Toshev, Z Chen, L Dinh, S Zhai, ... Advances in Neural Information Processing Systems 35, 25102-25116, 2022 | 133 | 2022 |
| Improving an object detector and extracting regions using superpixels G Shu, A Dehghan, M Shah Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 109 | 2013 |
| Automatic detection and tracking of pedestrians in videos with various crowd densities A Dehghan, H Idrees, AR Zamir, M Shah Pedestrian and evacuation dynamics 2012, 3-19, 2014 | 67 | 2014 |
| On detection, data association and segmentation for multi-target tracking Y Tian, A Dehghan, M Shah IEEE transactions on pattern analysis and machine intelligence 41 (9), 2146-2160, 2018 | 59 | 2018 |
| View independent vehicle make, model and color recognition using convolutional neural network A Dehghan, SZ Masood, G Shu, E Ortiz arXiv preprint arXiv:1702.01721, 2017 | 59 | 2017 |
| 4m: Massively multimodal masked modeling D Mizrahi, R Bachmann, O Kar, T Yeo, M Gao, A Dehghan, A Zamir Advances in Neural Information Processing Systems 36, 58363-58408, 2023 | 57 | 2023 |
| Binary quadratic programing for online tracking of hundreds of people in extremely crowded scenes A Dehghan, M Shah IEEE transactions on pattern analysis and machine intelligence 40 (3), 568-581, 2017 | 53 | 2017 |
| Slowfast-llava: A strong training-free baseline for video large language models M Xu, M Gao, Z Gan, HY Chen, Z Lai, H Gang, K Kang, A Dehghan arXiv preprint arXiv:2407.15841, 2024 | 31 | 2024 |
| 4m-21: An any-to-any vision model for tens of tasks and modalities R Bachmann, OF Kar, D Mizrahi, A Garjani, M Gao, D Griffiths, J Hu, ... Advances in Neural Information Processing Systems 37, 61872-61911, 2025 | 19 | 2025 |
| Mm1. 5: Methods, analysis & insights from multimodal llm fine-tuning H Zhang, M Gao, Z Gan, P Dufter, N Wenzel, F Huang, D Shah, X Du, ... arXiv preprint arXiv:2409.20566, 2024 | 17 | 2024 |
| Visual business recognition: a multimodal approach. AR Zamir, A Dehghan, M Shah ACM Multimedia 10 (2502081.2502174), 2013 | 15 | 2013 |
Mubarak ShahTrustee Chair Professor of Computer Science, University of Central FloridaOverená e-mailová adresa na: crcv.ucf.edu