| NTIRE 2023 challenge on efficient super-resolution: Methods and results Y Li, Y Zhang, R Timofte, L Van Gool, L Yu, Y Li, X Li, T Jiang, Q Wu, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023 | 118 | 2023 |
| A practical contrastive learning framework for single-image super-resolution G Wu, J Jiang, X Liu IEEE Transactions on Neural Networks and Learning Systems, 2023 | 46 | 2023 |
| NTIRE 2022 image inpainting challenge: Report A Romero, A Castillo, J Abril-Nova, R Timofte, R Das, S Hira, Z Pan, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2022 | 28 | 2022 |
| The robodepth challenge: Methods and advancements towards robust depth estimation L Kong, Y Niu, S Xie, H Hu, LX Ng, BR Cottereau, D Zhao, L Zhang, ... arXiv preprint arXiv:2307.15061, 2023 | 26 | 2023 |
| Glama: Joint spatial and frequency loss for general image inpainting Z Lu, J Jiang, J Huang, G Wu, X Liu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 23 | 2022 |
| No one idles: Efficient heterogeneous federated learning with parallel edge and server computation F Zhang, X Liu, S Lin, G Wu, X Zhou, J Jiang, X Ji International Conference on Machine Learning, 41399-41413, 2023 | 7 | 2023 |
| Incorporating transformer designs into convolutions for lightweight image super-resolution G Wu, J Jiang, Y Bai, X Liu arXiv preprint arXiv:2303.14324, 2023 | 7 | 2023 |
| Fully 1× 1 convolutional network for lightweight image super-resolution G Wu, J Jiang, K Jiang, X Liu Machine Intelligence Research, 1-15, 2024 | 6 | 2024 |
| Learning from history: Task-agnostic model contrastive learning for image restoration G Wu, J Jiang, K Jiang, X Liu Proceedings of the AAAI Conference on Artificial Intelligence 38 (6), 5976-5984, 2024 | 3 | 2024 |
| Transforming image super-resolution: a ConvFormer-based efficient approach G Wu, J Jiang, J Jiang, X Liu arXiv preprint arXiv:2401.05633, 2024 | 2 | 2024 |
| The third monocular depth estimation challenge J Spencer, F Tosi, M Poggi, RS Arora, C Russell, S Hadfield, R Bowden, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 2 | 2024 |
| Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs X Zhou, X Liu, F Zhang, G Wu, D Zhai, J Jiang, X Ji The Twelfth International Conference on Learning Representations, 2024 | 1 | 2024 |
| Fully Convolutional Network for Lightweight Image Super-Resolution G Wu, J Jiang, K Jiang, X Liu arXiv preprint arXiv:2307.16140, 2023 | 1 | 2023 |
| Exploiting Self-Supervised Constraints in Image Super-Resolution G Wu, J Jiang, K Jiang, X Liu arXiv preprint arXiv:2404.00260, 2024 | | 2024 |
| scDeepC3: scRNA-seq Deep Clustering by A Skip AutoEncoder Network with Clustering Consistency G Wu, J Jiang, X Liu bioRxiv, 2022.06. 05.494891, 2022 | | 2022 |
| Hybrid Cost Volume for Memory-Efficient Optical Flow Y Zhao, G Xu, G Wu ACM Multimedia 2024, 0 | | |
| Harmony in Diversity: Improving All-in-One Image Restoration via Multi-Task Collaboration G Wu, J Jiang, K Jiang, X Liu ACM Multimedia 2024, 0 | | |
| Convolution is All You Need for Image Super-Resolution G Wu, J Jiang, X Liu | | |
Junjun JiangHarbin Institute of Technology在 hit.edu.cn 的电子邮件经过验证
