| ECA-Net: Efficient channel attention for deep convolutional neural networks. Q Wang, B Wu, P Zhu, P Li, W Zuo, Q Hu In 2020 IEEE/CVF conference on computer vision and pattern recognition (CVPR …, 2020 | 2283 | 2020 |
| Mind the class weight bias: Weighted maximum mean discrepancy for unsupervised domain adaptation H Yan, Y Ding, P Li, Q Wang, Y Xu, W Zuo Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 534 | 2017 |
| Global second-order pooling convolutional networks Z Gao, J Xie, Q Wang, P Li Proceedings of the IEEE/CVF Conference on computer vision and pattern …, 2019 | 287 | 2019 |
| Is second-order information helpful for large-scale visual recognition? P Li, J Xie, Q Wang, W Zuo Proceedings of the IEEE international conference on computer vision, 2070-2078, 2017 | 264 | 2017 |
| Towards faster training of global covariance pooling networks by iterative matrix square root normalization P Li, J Xie, Q Wang, Z Gao Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 263 | 2018 |
| Visual contour tracking based on particle filters P Li, T Zhang, AEC Pece Image and Vision Computing 21 (1), 111-123, 2003 | 234 | 2003 |
| Robust and accurate iris segmentation in very noisy iris images P Li, X Liu, L Xiao, Q Song Image and vision computing 28 (2), 246-253, 2010 | 158 | 2010 |
| End-to-end image super-resolution via deep and shallow convolutional networks Y Wang, L Wang, H Wang, P Li IEEE Access 7, 31959-31970, 2019 | 151 | 2019 |
| Log-Euclidean kernels for sparse representation and dictionary learning P Li, Q Wang, W Zuo, L Zhang Proceedings of the IEEE international conference on computer vision, 1601-1608, 2013 | 151 | 2013 |
| Unscented Kalman filter for visual curve tracking P Li, T Zhang, B Ma Image and vision computing 22 (2), 157-164, 2004 | 148 | 2004 |
| Review on active contour model(snake model) PH Li, TW Zhang RUAN JIAN XUE BAO 11 (6), 751-757, 2000 | 147* | 2000 |
| Integrating boundary and center correlation filters for visual tracking with aspect ratio variation F Li, Y Yao, P Li, D Zhang, W Zuo, MH Yang Proceedings of the IEEE international conference on computer vision …, 2017 | 117 | 2017 |
| G2DeNet: Global Gaussian distribution embedding network and its application to visual recognition Q Wang, P Li, L Zhang Proceedings of the IEEE conference on computer vision and pattern …, 2017 | 110 | 2017 |
| A novel earth mover's distance methodology for image matching with gaussian mixture models P Li, Q Wang, L Zhang Proceedings of the IEEE International Conference on Computer Vision, 1689-1696, 2013 | 93 | 2013 |
| Iris recognition in non-ideal imaging conditions P Li, H Ma Pattern Recognition Letters 33 (8), 1012-1018, 2012 | 92 | 2012 |
| Multi-scale location-aware kernel representation for object detection H Wang, Q Wang, M Gao, P Li, W Zuo Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 86 | 2018 |
| Deep cnns meet global covariance pooling: Better representation and generalization Q Wang, J Xie, W Zuo, L Zhang, P Li IEEE transactions on pattern analysis and machine intelligence 43 (8), 2582-2597, 2020 | 79 | 2020 |
| Local log-Euclidean multivariate Gaussian descriptor and its application to image classification P Li, Q Wang, H Zeng, L Zhang IEEE transactions on pattern analysis and machine intelligence 39 (4), 803-817, 2016 | 74 | 2016 |
| RAID-G: Robust estimation of approximate infinite dimensional Gaussian with application to material recognition Q Wang, P Li, W Zuo, L Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2016 | 68 | 2016 |
| An adaptive binning color model for mean shift tracking P Li IEEE Transactions on Circuits and Systems for Video Technology 18 (9), 1293-1299, 2008 | 65 | 2008 |
