| A stochastic graph grammar for compositional object representation and recognition L Lin, T Wu, J Porway, Z Xu Pattern Recognition 42 (7), 1297-1307, 2009 | 159 | 2009 |
| Learning And-Or Model to Represent Context and Occlusion for Car Detection and Viewpoint Estimation T Wu, B Li, SC Zhu IEEE transactions on pattern analysis and machine intelligence 38 (9), 1829-1843, 2016 | 133* | 2016 |
| face detection with end-to-end integration of a ConvNet and a 3D model Y Li, B Sun, T Wu, Y Wang European Conference on Computer Vision, 420-436, 2016 | 120 | 2016 |
| The thermal infrared visual object tracking VOT-TIR2015 challenge results M Felsberg, A Berg, G Hager, J Ahlberg, M Kristan, J Matas, A Leonardis, ... Proceedings of the IEEE International Conference on Computer Vision …, 2015 | 106 | 2015 |
| Design sparse features for age estimation using hierarchical face model J Suo, T Wu, S Zhu, S Shan, X Chen, W Gao 2008 8th IEEE International Conference on Automatic Face & Gesture …, 2008 | 97 | 2008 |
| A numerical study of the bottom-up and top-down inference processes in and-or graphs T Wu, SC Zhu International journal of computer vision 93 (2), 226-252, 2011 | 90 | 2011 |
| Online object tracking, learning and parsing with and-or graphs Y Lu, T Wu, S Chun Zhu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 87 | 2014 |
| Auto-Context R-CNN B Li, T Wu, L Zhang, R Chu arXiv preprint arXiv:1807.02842, 2018 | 64* | 2018 |
| Discriminatively trained and-or tree models for object detection X Song, T Wu, Y Jia, SC Zhu Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 64 | 2013 |
| Learn to grow: A continual structure learning framework for overcoming catastrophic forgetting X Li, Y Zhou, T Wu, R Socher, C Xiong International Conference on Machine Learning, 3925-3934, 2019 | 55 | 2019 |
| Compositional boosting for computing hierarchical image structures TF Wu, GS Xia, SC Zhu 2007 IEEE Conference on Computer Vision and Pattern Recognition, 1-8, 2007 | 54 | 2007 |
| Deep learning for remote sensing image understanding L Zhang, GS Xia, T Wu, L Lin, XC Tai Journal of Sensors 2016, 2016 | 48 | 2016 |
| Face video retrieval via deep learning of binary hash representations Z Dong, S Jia, T Wu, M Pei Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 34 | 2016 |
| Modeling occlusion by discriminative and-or structures B Li, W Hu, T Wu, SC Zhu Proceedings of the IEEE International Conference on Computer Vision, 2560-2567, 2013 | 34 | 2013 |
| Vision-based integrated mobile robotic system for real-time applications in construction K Asadi, H Ramshankar, H Pullagurla, A Bhandare, S Shanbhag, P Mehta, ... Automation in Construction 96, 470-482, 2018 | 31 | 2018 |
| Bayesian inference for layer representation with mixed markov random field RX Gao, TF Wu, SC Zhu, N Sang International Workshop on Energy Minimization Methods in Computer Vision and …, 2007 | 30 | 2007 |
| The grey theory and the preliminary probe into information acquisition technology Q Zhao, J Gao, T Wu, L Lu International Conference on Information Acquisition, 2004. Proceedings., 402-404, 2004 | 30 | 2004 |
| Learning reconfigurable scene representation by tangram model J Zhu, T Wu, SC Zhu, X Yang, W Zhang 2012 IEEE Workshop on the Applications of Computer Vision (WACV), 449-456, 2012 | 26 | 2012 |
| Learning attraction field representation for robust line segment detection N Xue, S Bai, F Wang, GS Xia, T Wu, L Zhang Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 25 | 2019 |
| Learning near-optimal cost-sensitive decision policy for object detection T Wu, SC Zhu Proceedings of the IEEE International Conference on Computer Vision, 753-760, 2013 | 22 | 2013 |
song-chun zhuProfessor of Statistics and Computer Science, UCLAVerified email at stat.ucla.edu
