Qilong Wang

qlwang@tju.edu.cn

135 Yaguan Road
300350
Tianjin
China

github.com/csqlwang

About Me

I am a full professor at the College of Intelligence and Computing of Tianjin University. Previously, I joined Tianjin University as an Assistant Professor in 2018. I received the B.S. degree and M.Sc. degree from Heilongjiang University in 2011 and 2014, and the Ph.D. degree from Dalian University of Technology under the supervision of Prof. Peihua Li in 2018. My current research interests are on computer vision and deep learning, particularly multimodal large language model for specific tasks, deep architectures design and optimization based on high-order statistical modeling.

News!

 

[2024-09-26] One paper is accepted to NeurIPS 2024.

[2024-09-08] One paper is accepted to IEEE T-NNLS.

[2024-04-23] One paper is accepted to IEEE T-NNLS.

[2024-04-10] One paper is accepted to IEEE T-NNLS.

[2024-03-07] I was awarded the WuWenJun AI Excellent Young Scientist.

[2024-02-27] One paper is accepted to CVPR 2024.

[2024-02-21] One paper is accepted to IEEE T-IP.

[2023-09-23] One paper is accepted to IEEE T-PAMI.

[2023-09-22] One paper is accepted to IEEE T-NNLS.

[2023-07-14] One paper is accepted to ICCV 2023.

[2023-02-28] One paper is accepted to CVPR 2023.

[2022-09-15] One paper is accepted to NeurIPS 2022.

[2022-03-14] One paper is accepted to IEEE T-IP.

[2022-03-03] One paper is accepted to CVPR 2022.

[2021-12-24] One paper is accepted to IEEE T-IP.

[2021-09-29] One paper is accepted to NeurIPS 2021.

[2021-07-27] One paper is accepted to ICCV 2021.

[2021-03-27] One paper is accepted to CVPR 2021.

[2020-09-15] I was awarded the excellent doctoral dissertation of Chinese Association for Artificial Intelligence (CAAI). [Official news of CAAI and SOHU]

[2020-02-27] Three papers are accepted to CVPR 2020.

[2020-02-11] One paper is accepted to IEEE T-PAMI.

[2019-03-03] Two papers are accepted to CVPR 2019.

[2018-11-28] We organizded a Tutorial in PRCV 2018, and PPT can be download Here.

[2018-09-05] One paper is accepted to NIPS 2018.

[2018-05-21] Two papers are accepted to IJCAI 2018.

[2018-05-15] I am supported by program for Post-doctoral Innovative Talents.

[2018-02-19] Two papers are accepted to CVPR 2018.

[2017-07-17] One paper is accepted to ICCV 2017.

[2017-03-18] Two papers are accepted to CVPR 2017. One of them was selected for oral presentation (~2.65% acceptance rate).

Preprint Papers

  1. Jiangtao Xie, Ruiren Zeng, Qilong Wang, Ziqi Zhou, Peihua Li. So-ViT: Mind Visual Tokens for Vision Transformer. CoRR abs/2104.10935, 2021. [arXiv][Code] (We make an attempt to exploit visual tokens of vision Transformer by using second-order pooling for  effective visual classification)

Journal Papers

  1. Qilong Wang, Zhaolin Zhang, Mingze Gao, Jiangtao Xie, Pengfei Zhu, Peihua Li, Wangmeng Zuo and Qinghua Hu. Towards A Deeper Understanding of Global Covariance Pooling in Deep Learning: An Optimization Perspective. IEEE T-PAMI, 45(12): 15802-15819, 2023. [PDF][Code]
  2. Qilong Wang, Jiangtao Xie, Wangmeng Zuo, Lei Zhang and Peihua Li. Deep CNNs Meet Global Covariance Pooling: Better Representation and Generalization. IEEE T-PAMI 43(8): 2582-2597, 2021. [PDF][Code][arXiv]
  3. Peihua Li, Qilong Wang, Hui Zeng and Lei Zhang. Local Log-Euclidean Multivariate Gaussian Descriptor and Its Application to Image Classification. IEEE T-PAMI 39(4): 803-817, 2017. [PDF][Code]
  4. Qilong Wang, Yiwen Wu, Wangmeng Zuo, Qinghua Hu. Layer-Specific Knowledge Distillation for Class Incremental Semantic Segmentation. IEEE T-IP, 2024 (33):1977-1989. [PDF][Code]
  5. Qilong Wang, Qiyao Hu, Zilin Gao, Peihua Li and Qinghua Hu. AMS-Net: Modeling Adaptive Multi-granularity Spatio-temporal Cues for Video Action Recognition. IEEE T-NNLS, 2023. [PDF][Code]
  6. Pengfei Zhu, Jialu Li, Zhe Dong, Qinghua Hu, Xiao Wang, Qilong Wang*. CCP-GNN: Competitive Covariance Pooling for Improving Graph Neural Networks. IEEE T-NNLS, 2024. [PDF][Code] (*The corresponding author)
  7. Xiaojie Yin, Bing Cao, Qinghua Hu, Qilong Wang*. D-OpenMax: Discriminative OpenMax for Robust Realistic Open-Set Recognition. IEEE T-NNLS, 2024. [PDF][Code] (*The corresponding author)
  8. Tianqi Ma, Qilong Wang*, Hongzhi Zhang, Wangmeng Zuo. Delving Deeper into Pixel Prior for Box-Supervised Semantic Segmentation. IEEE T-IP, 2022 (31):1406-1417. [PDF][Code] (*The corresponding author)
  9. Qilong Wang, Xiaoxiao Lu, Peihua Li, Zhenguo Gao, Yongri Piao. An Information Geometry Based Distance between High-dimensional Covariances for Scalable Classification. IEEE T-CSVT 28(10): 2449-2459, 2018. [PDF]

 

Conference Papers

  1. Yuwei Tang, Zhenyi Lin, Qilong Wang*, Pengfei Zhu, Qinghua Hu. AMU-Tuning: Effective Logit Bias for CLIP-based Few-shot Learning. 37th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2024. [PDF][Code](*The corresponding author)
  2. Mingze Gao, Qilong Wang*, Zhenyi Lin, Pengfei Zhu, Qinghua Hu, Jingbo Zhou. Tuning Pre-trained Model via Moment Probing. 19th IEEE International Conference on Computer Vision (ICCV), 2023. [PDF][Code](*The corresponding author)
  3. Qilong Wang, Mingze Gao, Zhaolin Zhang, Jiangtao Xie, Peihua Li, Qinghua Hu. DropCov: A Simple yet Effective Method for Improving Deep Architectures. Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. [PDF][Code]
  4. Jiangtao Xie, Fei Long, Jiaming Lv, Qilong Wang, Peihua Li. Joint Distribution Matters: Deep Brownian Distance Covariance for Few-Shot Classification. 35th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2022. (Oral, acceptance rate: ~5%) [PDF][Code]
  5. Zilin Gao, Qilong Wang, Bingbing Zhang, Qinghua Hu, Peihua Li. Temporal-attentive Covariance Pooling Networks for Video Recognition. Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), 2021. [PDF][Code]
  6. Bowen Dong, Zitong Huang, Yuelin Guo, Qilong Wang, Zhenxing Niu, Wangmeng Zuo. Boosting Weakly Supervised Object Detection via Learning Bounding Box Adjusters. 18th IEEE International Conference on Computer Vision (ICCV), 2021. [arXiv][Code]
  7. Longyin Wen, Dawei Du, Pengfei Zhu, Qinghua Hu, Qilong Wang, Liefeng Bo, Siwei Lyu. Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark. 34th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2021. [PDF][arXiv][Code]
  8. 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. 33th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020. [PDF][arXiv][Code]
  9. Qilong Wang, Banggu Wu, Pengfei Zhu, Peihua Li, Wangmeng Zuo, Qinghua Hu. ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks. 33th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020.[PDF][arXiv][Code] (Most influential CVPR papers recommended by Paper Digest)
  10. Qilong Wang, Peihua Li, Qinghua Hu, Pengfei Zhu, Wangmeng Zuo. Deep Global Generalized Gaussian Networks. 32th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF] [Code]
  11. Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li. Global Second-order Pooling Convolutional Networks. 32th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019. [PDF][Code]
  12. Qilong Wang*, Zilin Gao*, Jiangtao Xie, Wangmeng Zuo, Peihua Li. Global Gated Mixture of Second-order Pooling for Improving Deep Convolutional Neural Networks. Thirty-second Conference on Neural Information Processing Systems (NeurIPS), 2018. [PDF][Supplemental][Code] (*The first two authors contribute equally to this work)
  13. Hao Wang, Qilong Wang, Mingqi Gao, Peihua Li, Wangmeng Zuo. Multi-scale Location-aware Kernel Representation for Object Detection. 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF][arXiv] [Code] (The first attempt to integrate higher-order statistics into object detection task)
  14. Peihua Li, Jiangtao Xie, Qilong Wang, Zilin Gao. Towards Faster Training of Global Covariance Pooling Networks by Iterative Matrix Square Root Normalization. 31th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018. [PDF][arXiv] [Code] (Speed up training of covariance pooling networks)
  15. Peihua Li, Jiangtao Xie, Qilong Wang, Wangmeng Zuo. Is Second-Order Information Helpful for Large-Scale Visual Recognition? 16th IEEE International Conference on Computer Vision (ICCV), 2017. [PDF] [Code] (The work shows matrix power normalized covariance pooling is very effective on large-scale classification task)
  16. Qilong Wang, Peihua Li, Lei Zhang. G2DeNet: Global Gaussian Distribution Embedding Network and Its Application to Visual Recognition. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. (Oral, acceptance rate: 2.65%) [PDF] [Code] (Embedding a global trainable Gaussian distribution (square root SPD matrix) into deep CNNs, obtaining state-of-the-art results on FGVC task)
  17. Hongliang Yan, Yukang Ding, Peihua Li, Qilong Wang, Yong Xu, Wangmeng Zuo. Mind the Class Weight Bias: Weighted Maximum Mean Discrepancy for Unsupervised Domain Adaptation. 30th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017. [PDF] [Code]
  18. Qilong Wang, Peihua Li, Wangmeng Zuo, Lei Zhang. RAID-G: Robust Estimation of Approximate Infinite Dimensional Gaussian with Application to Material Recognition. 29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. [PDF] [Code] (A Gaussian descriptor with robust covariance estimation, achieving state-of-the-art results on texture classification task)
  19. Qilong Wang, Xiaona Deng, Peihua Li, Lei Zhang. Ask the Dictionary: Soft-Assignment Location-Orientation Pooling for Image Classification. 22th International Conference on Image Processing (ICIP), 2015. (Best 10% Paper Award) [PDF]
  20. Peihua Li, Xiaoxiao Lu, Qilong Wang. From Dictionary of Visual Words to Subspaces: Locality-constrained Affine Subspace Coding. 28th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. [Project Page]
  21. Qilong Wang, Wangmeng Zuo, Lei Zhang, Peihua Li. Shrinkage Expansion Adaptive Metric Learning. 13th European Conference on Computer Vision (ECCV), 2014. [PDF] [Code]
  22. Peihua Li, Qilong Wang, Lei Zhang. A Novel Earth Mover's Distance Methodology for Image Matching with Gaussian Mixture Models. 14th IEEE International Conference on Computer Vision (ICCV), 2013. [Project Page]
  23. Peihua Li, Qilong Wang, Wangmeng Zuo, Lei Zhang. Log-Euclidean Kernels for Sparse Representation and Dictionary Learning. 14th IEEE International Conference on Computer Vision (ICCV), 2013. [Project Page]
  24. Peihua Li, Qilong Wang. Local Log-Euclidean Covariance Matrix (L2ECM) for Image Representation and Its Applications. 12th European Conference on Computer Vision (ECCV), 2012. [PDF] [Code]

 

Honors

  • *The WuWenJun AI Excellent Young Scientist, 2023

  • *Second prize of Tianjin Prize for Progress in Science and Technology, 2023 (3/8)

  • *Second prize of Tianjin Prize for Progress in Science and Technology, 2022 (1/8)

  • *The excellent doctoral dissertation of Chinese Association for Artificial Intelligence (CAAI), 2020

  • *ICIP2015 Best 10% Paper Award

Academic Service

Journal Reviewer

IEEE Transactions on Pattern Analysis and Machine Intelligence

International Journal of Computer Vision

IEEE Transactions on Image Processing

IEEE Transactions on Neural Networks and Learning Systems

IEEE Transactions on Circuits and Systems for Video Technology

IEEE Transactions on Multimedia


Conference Reviewer

CVPR 2018-2023, ICCV 2019 2021 2023, ICML 2021- 2024, ICLR 2021-2024, NeurIPS 2020-2023, ECCV 2020 2022 2024

PC for AAAI 2019-2021, IJCAI 2019 2020 2022-2024

SPC for IJCAI 2021, SPC for AAAI 2022

Area Chair for CVPR 2024, CVPR 2025