Gang Wu

Orcid: 0009-0007-5003-3117

Affiliations:
  • Harbin Institute of Technology, School of Computer Science and Technology, Harbin, China


According to our database1, Gang Wu authored at least 16 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
A Practical Contrastive Learning Framework for Single-Image Super-Resolution.
IEEE Trans. Neural Networks Learn. Syst., November, 2024

Transforming Image Super-Resolution: A ConvFormer-Based Efficient Approach.
IEEE Trans. Image Process., 2024

Harmony in Diversity: Improving All-in-One Image Restoration via Multi-Task Collaboration.
Proceedings of the 32nd ACM International Conference on Multimedia, MM 2024, Melbourne, VIC, Australia, 28 October 2024, 2024

Exploiting Self-Supervised Constraints in image Super-Resolution.
Proceedings of the IEEE International Conference on Multimedia and Expo, 2024

Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Improving Domain Generalization in Self-supervised Monocular Depth Estimation via Stabilized Adversarial Training.
Proceedings of the Computer Vision - ECCV 2024, 2024


Learning from History: Task-agnostic Model Contrastive Learning for Image Restoration.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Fully 1×1 Convolutional Network for Lightweight Image Super-Resolution.
CoRR, 2023

The RoboDepth Challenge: Methods and Advancements Towards Robust Depth Estimation.
CoRR, 2023

Incorporating Transformer Designs into Convolutions for Lightweight Image Super-Resolution.
CoRR, 2023

No One Idles: Efficient Heterogeneous Federated Learning with Parallel Edge and Server Computation.
Proceedings of the International Conference on Machine Learning, 2023

NTIRE 2023 Challenge on Efficient Super-Resolution: Methods and Results.
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Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

GLaMa: Joint Spatial and Frequency Loss for General Image Inpainting.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, 2022

2021
A Practical Contrastive Learning Framework for Single Image Super-Resolution.
CoRR, 2021


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