Details on papers, code, project, etc., can be found at http://peihuali.org/home.html

Peihua Li is a professor of Dalian University of Technology. He received Ph.D degree from Harbin Institute of Technology in 2003, and then worked for one year as a postdoctoral fellow at INRIA/IRISA, France. He achieved the honorary nomination of National Excellent Doctoral dissertation in China. He was supported by Program for New Century Excellent Talents in University of Chinese Ministry of Education. His team won the 1st place in large-scale iNaturalist Challenge spanning 8000 species at FGVC5 CVPR2018, 2nd place in Alibaba Large-scale Image Search Challenge 2015, and 4th place in Noisy Iris Challenge Evaluation I. His research topics include deep learning, computer vision and pattern recognition, focusing on image/video recognition, object detection and semantic segmentation. He has published papers in top journals such as IEEE TPAMI/TIP/TCSVT and top conferences including ICCV/CVPR/ECCV/NeurIPS. As principal investigator, he receives funds from National Natural Sceince Foundation of China (NSFC), Chinese Ministry of Education and Huawei Technologies Co., Ltd. He is an assoicate editor of IEEE Trans. On Image Processing.
 

Representative publications

1. Jiangtao Xie*, Fei Long*, Jiaming Lv, Qilong Wang, Peihua Li. Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2022. *Equal contribution. (Oral presentation, acceptance rate ~5%)

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3.  Zilin Gao, Qilong Wang, Bingbing Zhang, Qinghua Hu and Peihua Li. Temporal-adaptive Covariance Pooling Networks for Video Recognition. Advances in Neural Information Processing Systems (NeurIPS), 2021.

4.  Qilong Wang, Jiangtao Xie, Wangmeng Zuo, Lei Zhang and Peihua Li. Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 2021.

5.  Qilong Wang, Li Zhang, Banggu Wu, Dongwei Ren, Peihua Li, Wangmeng Zuo, Qinghua Hu. What Deep CNNs Benefit from Global Covariance Pooling: An Optimization Perspective. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2020.

6. Qilong Wang, Banggu Wu, Pengfei Zhu, Peihua Li, Wangmeng Zuo, Qinghua Hu. ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2020.

7. Zilin Gao, Jiangtao Xie, Qilong Wang and Peihua Li. Global Second-order Pooling Convolutional Networks. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2019.

8. Qilong Wang, Peihua Li, Qinghua Hu, Pengfei Zhu, Wangmeng Zuo. Deep Global Generalized Gaussian Networks. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2019.

9. Peihua Li, Jiangtao Xie, Qilong Wang and Zilin Gao. Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization. IEEE Int. Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 947-955, 2018

10. Peihua Li, Jiangtao Xie, Qilong Wang and Wangmeng Zuo. Is Second-order Information Helpful for Large-scale Visual Recognition? IEEE Int. Conf. on Computer Vision (ICCV),  pp. 2070-2078, 2017.

11. Qilong Wang*, Zilin Gao*, Jiangtao Xie, Wangmeng Zuo and Peihua Li. Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks. Advances in Neural Information Processing Systems (NIPS), 2018.

12. Peihua Li, Qilong Wang, Hui Zeng, Lei Zhang. Local Log-Euclidean Multivariate Gaussian Descriptor and Its Application to Image Classification. IEEE Trans. on Pattern Analysis and Machine Intelligence (TPAMI), 39(4): 803-817, 2017.

13. Qilong Wang, Peihua Li, Lei Zhang. G2DeNet: Global Gaussian Distribution Embedding Network and Its Application to Visual Recognition. Int. Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 2730-2739, 2017. (Oral presentation, acceptance rate 2.7%)

14. Qilong Wang, Peihua Li, Wangmeng Zuo, Lei Zhang. RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian with Application to Materiel Recognition. Int. Conf. on Computer Vision and Pattern Recognition (CVPR), pp. 4433-4441, 2016.

15. Peihua Li, Xiaoxiao Lu, Qilong Wang. From Dictionary of Visual Words to Subspaces: Locality-constrained Affine Subspace Coding. Int. Conf. on Computer Vision and Pattern Recognition (CVPR), 2015

16. Qilong Wang, Wangmeng Zuo, Lei Zhang, Peihua Li. Shrinkage Expansion Adaptive Metric Learning. European Conf. on Computer Vision, ECCV (7) 2014 : 456-471

17. Peihua Li, Qilong Wang, Lei Zhang. A Novel Earth Mover's Distance Methodology for Image Matching with Gaussian Mixture Models. IEEE Int. Conf. on Computer Vision (ICCV), 2013.

18. Peihua Li, Qilong Wang, Wangmeng Zuo, Lei Zhang. Log-Euclidean Kernels for Sparse Representation and Dictionary Learning. IEEE Int. Conf. on Computer Vision (ICCV), 2013.

19. Peihua Li, Qilong Wang. Local Log-Euclidean Covariance Matrix (L2ECM) for Image Representation and Its Applications. European Conf. on Computer Vision, ECCV (3) 2012 : 469-482.