E-mail

Scholar

Github @Aitical

Wechat @w965813422

Gang Wu （吴刚）

PhD student @ HIT

I obtained my Bachelor degree from Soochow University in 2020.

Currently, I am a Ph.D. student at Harbin Institute of Technology, where I am under the supervision of Prof. Junjun Jiang.

Mainly intrest in computer vision, especially in Low-level Vision and Representation Learning.

News

• 2024-07: One first author paper was accepted in ACM MultiMedia 2024.
• 2024-07: One paper to appear in ECCV 2024 .
• 2024-04: One first author paper was accepted in ICME 2024 (Oral).
• 2024-01: One first author paper was accepted in Machine Intelligence Research.
• 2024-01: One paper to appear in ICLR 2024.
• 2023-12: One first author paper was accepted in AAAI 2024.
• 2023-05: One first author paper was accepted in IEEE Trans. Neural Networks Learn. Syst.
• 2023-04: One paper to appear in ICML 2023.
• 2023-04: One paper to appear in CVPRW 2022.

Education

Harbin Institute of Technology
Ph.D. student, 2020 ~ present.

Soochow University
B.Eng., Major in Computer Science, Sep 2016 - Jul 2020.

Publications

	Under Review Debiased All-in-one Image Restoration with Task Uncertainty Regularization Gang Wu, Junjun Jiang, Yijun Wang, Kui Jiang, Xianming Liu ​ ​ ​ [Code] and [Paper] are coming soon. ​ ​ ​ ​ ​ ​ ​ ​
	ACM MM 24 Harmony in Diversity: Improving All-in-One Image Restoration via Multi-Task Collaboration Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu ​ ​ ​ [Code] [Paper] ​ ​ ​ ​ ​ ​ ​ ​
	ICME, 2024 (Oral) Exploiting Self-Supervised Constraints in Image Super-Resolution Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu ​ ​ ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ ​ ​
	AAAI, 2024 Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu ​ ​ ​ [Project] ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ 🔥 The extended journal version is under review. ​ ​
	Machine Intelligence Research, 2024 Fully 1×1 Convolutional Network for Lightweight Image Super-Resolution Gang Wu, Junjun Jiang, Kui Jiang, Xianming Liu ​ ​ ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ ​ ​
	IEEE Trans. Neural Networks Learn. Syst., 2023 A Practical Contrastive Learning Framework for Single-Image Super-Resolution Gang Wu, Junjun Jiang, Junpeng Jiang, Xianming Liu ​ ​ ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ ​ ​
	ECCV 2024 Improving Domain Generalization in Self-Supervised Monocular Depth Estimation via Stabilized Adversarial Training Yuanqi Yao, Gang Wu, Kui Jiang, Siao Liu, Jian Kuai, Xianming Liu, and Junjun Jiang ​ ​ ​ ​ ​ ​ ​ ​ ​ ​
	ICLR 2024 Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs Xiong Zhou, Xianming Liu, Feilong Zhang, Gang Wu, Deming Zhai, Junjun Jiang, Xiangyang Ji ​ ​ ​ [Code] ​ [Paper] ​ ​ ​ ​ ​ ​ ​ ​
	ICML 2023 No one idles: Efficient heterogeneous federated learning with parallel edge and server computation Feilong Zhang, Xianming Liu, Shiyi Lin, Gang Wu, Xiong Zhou, Junjun Jiang, Xiangyang Ji Junjun Jiang, Xianming Liu ​ ​ ​ [Code] [Paper] ​ ​ ​ ​ ​ ​ ​ ​ ​
	Arxiv Incorporating transformer designs into convolutions for lightweight image super-resolution Gang Wu, Junjun Jiang, Yuanchao Bai, Xianming Liu ​ ​ ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ ​ ​
	Arxiv Transforming Image Super-Resolution: A ConvFormer-based Efficient Approach Gang Wu, Junjun Jiang, Junpeng Jiang, Xianming Liu ​ ​ ​ [Code] ​ [Arxiv] ​ ​ ​ ​ ​ ​ ​ ​

Experience

MEGVII
2022.4 ~ 2022.10. Research Intern.

Academic Service & Awards

Competition Awards

Reviewer