| Deepid-net: Deformable deep convolutional neural networks for object detection W Ouyang, X Wang, X Zeng, S Qiu, P Luo, Y Tian, H Li, S Yang, Z Wang, ... Proceedings of the IEEE conference on computer vision and pattern …, 2015 | 386* | 2015 |
| T-cnn: Tubelets with convolutional neural networks for object detection from videos K Kang, H Li, J Yan, X Zeng, B Yang, T Xiao, C Zhang, Z Wang, R Wang, ... IEEE Transactions on Circuits and Systems for Video Technology 28 (10), 2896 …, 2017 | 201 | 2017 |
| Multi-stage contextual deep learning for pedestrian detection X Zeng, W Ouyang, X Wang Proceedings of the IEEE International Conference on Computer Vision, 121-128, 2013 | 162 | 2013 |
| Modeling mutual visibility relationship in pedestrian detection W Ouyang, X Zeng, X Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2013 | 144 | 2013 |
| Deepid-net: multi-stage and deformable deep convolutional neural networks for object detection W Ouyang, P Luo, X Zeng, S Qiu, Y Tian, H Li, S Yang, Z Wang, Y Xiong, ... arXiv preprint arXiv:1409.3505, 2014 | 117 | 2014 |
| Deep learning of scene-specific classifier for pedestrian detection X Zeng, W Ouyang, M Wang, X Wang European Conference on Computer Vision, 472-487, 2014 | 109 | 2014 |
| Crafting gbd-net for object detection X Zeng, W Ouyang, J Yan, H Li, T Xiao, K Wang, Y Liu, Y Zhou, B Yang, ... IEEE transactions on pattern analysis and machine intelligence 40 (9), 2109-2123, 2017 | 96 | 2017 |
| Gated bi-directional cnn for object detection X Zeng, W Ouyang, B Yang, J Yan, X Wang European conference on computer vision, 354-369, 2016 | 80 | 2016 |
| Gs3d: An efficient 3d object detection framework for autonomous driving B Li, W Ouyang, L Sheng, X Zeng, X Wang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2019 | 48 | 2019 |
| Learning mutual visibility relationship for pedestrian detection with a deep model W Ouyang, X Zeng, X Wang International Journal of Computer Vision 120 (1), 14-27, 2016 | 47 | 2016 |
| Partial occlusion handling in pedestrian detection with a deep model W Ouyang, X Zeng, X Wang IEEE Transactions on Circuits and Systems for Video Technology 26 (11), 2123 …, 2015 | 34 | 2015 |
| Single-pedestrian detection aided by two-pedestrian detection W Ouyang, X Zeng, X Wang IEEE transactions on pattern analysis and machine intelligence 37 (9), 1875-1889, 2014 | 34 | 2014 |
| Visual importance and distortion guided deep image quality assessment framework J Guan, S Yi, X Zeng, WK Cham, X Wang IEEE Transactions on Multimedia 19 (11), 2505-2520, 2017 | 28 | 2017 |
| Learning deep representation with large-scale attributes W Ouyang, H Li, X Zeng, X Wang Proceedings of the IEEE International Conference on Computer Vision, 1895-1903, 2015 | 19 | 2015 |
| Window-object relationship guided representation learning for generic object detections X Zeng, W Ouyang, X Wang arXiv preprint arXiv:1512.02736, 2015 | 5 | 2015 |
| Deep Neural Networks for Object Detection X Zeng PQDT-Global, 2016 | 2 | 2016 |
| Adapting Object Detectors with Conditional Domain Normalization P Su, K Wang, X Zeng, S Tang, D Chen, D Qiu, X Wang arXiv preprint arXiv:2003.07071, 2020 | 1 | 2020 |
| Monocular 3D Object Detection with Decoupled Structured Polygon Estimation and Height-Guided Depth Estimation. Y Cai, B Li, Z Jiao, H Li, X Zeng, X Wang AAAI, 10478-10485, 2020 | | 2020 |
