| Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising K Zhang, W Zuo, Y Chen, D Meng, L Zhang IEEE transactions on image processing 26 (7), 3142-3155, 2017 | 7989 | 2017 |
| Infrared patch-image model for small target detection in a single image C Gao, D Meng, Y Yang, Y Wang, X Zhou, AG Hauptmann IEEE transactions on image processing 22 (12), 4996-5009, 2013 | 884 | 2013 |
| Progressive image deraining networks: A better and simpler baseline D Ren, W Zuo, Q Hu, P Zhu, D Meng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 869 | 2019 |
| Meta-weight-net: Learning an explicit mapping for sample weighting J Shu, Q Xie, L Yi, Q Zhao, S Zhou, Z Xu, D Meng Advances in neural information processing systems 32, 2019 | 833 | 2019 |
| Weighted nuclear norm minimization and its applications to low level vision S Gu, Q Xie, D Meng, W Zuo, X Feng, L Zhang International journal of computer vision 121, 183-208, 2017 | 792 | 2017 |
| Self-paced curriculum learning L Jiang, D Meng, Q Zhao, S Shan, A Hauptmann Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 582 | 2015 |
| Co-saliency detection via a self-paced multiple-instance learning framework D Zhang, D Meng, J Han IEEE transactions on pattern analysis and machine intelligence 39 (5), 865-878, 2016 | 524 | 2016 |
| Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery Q Xie, Q Zhao, D Meng, Z Xu IEEE transactions on pattern analysis and machine intelligence 40 (8), 1888-1902, 2017 | 466* | 2017 |
| Semi-supervised transfer learning for image rain removal W Wei, D Meng, Q Zhao, Z Xu, Y Wu Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 431 | 2019 |
| Robust online matrix factorization for dynamic background subtraction H Yong, D Meng, W Zuo, L Zhang IEEE transactions on pattern analysis and machine intelligence 40 (7), 1726-1740, 2017 | 419* | 2017 |
| Convolutional sparse coding for image super-resolution S Gu, W Zuo, Q Xie, D Meng, X Feng, L Zhang Proceedings of the IEEE International Conference on Computer Vision, 1823-1831, 2015 | 416 | 2015 |
| Decidenet: Counting varying density crowds through attention guided detection and density estimation J Liu, C Gao, D Meng, AG Hauptmann Proceedings of the IEEE conference on computer vision and pattern …, 2018 | 412 | 2018 |
| Self-paced learning with diversity L Jiang, D Meng, SI Yu, Z Lan, S Shan, A Hauptmann Advances in neural information processing systems 27, 2014 | 412 | 2014 |
| A generalized iterated shrinkage algorithm for non-convex sparse coding W Zuo, D Meng, L Zhang, X Feng, D Zhang Proceedings of the IEEE international conference on computer vision, 217-224, 2013 | 401 | 2013 |
| MHF-Net: An interpretable deep network for multispectral and hyperspectral image fusion Q Xie, M Zhou, Q Zhao, Z Xu, D Meng IEEE Transactions on Pattern Analysis and Machine Intelligence 44 (3), 1457-1473, 2020 | 380* | 2020 |
| Hyperspectral image restoration via total variation regularized low-rank tensor decomposition Y Wang, J Peng, Q Zhao, Y Leung, XL Zhao, D Meng IEEE Journal of Selected Topics in Applied Earth Observations and Remote …, 2017 | 368 | 2017 |
| Decomposable nonlocal tensor dictionary learning for multispectral image denoising Y Peng, D Meng, Z Xu, C Gao, Y Yang, B Zhang Proceedings of the IEEE Conference on Computer Vision and Pattern …, 2014 | 365 | 2014 |
| A model-driven deep neural network for single image rain removal H Wang, Q Xie, Q Zhao, D Meng Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 353 | 2020 |
| Variational denoising network: Toward blind noise modeling and removal Z Yue, H Yong, Q Zhao, D Meng, L Zhang Advances in neural information processing systems 32, 2019 | 352 | 2019 |
| Robust multi-exposure image fusion: a structural patch decomposition approach K Ma, H Li, H Yong, Z Wang, D Meng, L Zhang IEEE Transactions on Image Processing 26 (5), 2519-2532, 2017 | 345 | 2017 |
Qian ZhaoXi'an Jiaotong University在 xjtu.edu.cn 的电子邮件经过验证
