| Nonlocally Centralized Sparse Representation for Image Restoration W Dong, L Zhang, G Shi, X Li IEEE Trans. on Image Processing 22 (4), 1620-1630, 2013 | 1544 | 2013 |
| Image deblurring and super-resolution by adaptive sparse domain selection and adaptive regularization W Dong, L Zhang, G Shi, X Wu IEEE Transactions on image processing 20 (7), 1838-1857, 2011 | 1480 | 2011 |
| Two-stage image denoising by principal component analysis with local pixel grouping L Zhang, W Dong, D Zhang, G Shi Pattern recognition 43 (4), 1531-1549, 2010 | 825 | 2010 |
| Nonlocal Image Restoration with Bilateral Variance Estimation: a Low-rank Approach W Dong, G Shi, X Li IEEE Trans. on Image Processing 22 (2), 700-711, 2013 | 697 | 2013 |
| Sparsity-based image denoising via dictionary learning and structural clustering W Dong, X Li, L Zhang, G Shi CVPR 2011, 457-464, 2011 | 590 | 2011 |
| Compressive sensing via nonlocal low-rank regularization W Dong, G Shi, X Li, Y Ma, F Huang IEEE transactions on image processing 23 (8), 3618-3632, 2014 | 541 | 2014 |
| Sparse Representation based Image Interpolation with Nonlocal Autoregressive Modeling W Dong, L Zhang, R Lukac, G Shi IEEE Trans. on Image Processing 22 (4), 1382-1394, 2013 | 416 | 2013 |
| Hyperspectral image super-resolution via non-negative structured sparse representation W Dong, F Fu, G Shi, X Cao, J Wu, G Li, X Li IEEE Transactions on Image Processing 25 (5), 2337-2352, 2016 | 405 | 2016 |
| Denoising prior driven deep neural network for image restoration W Dong, P Wang, W Yin, G Shi, F Wu, X Lu IEEE transactions on pattern analysis and machine intelligence 41 (10), 2305 …, 2018 | 346 | 2018 |
| Centralized sparse representation for image restoration W Dong, L Zhang, G Shi 2011 International Conference on Computer Vision, 1259-1266, 2011 | 306 | 2011 |
| MetaIQA: Deep meta-learning for no-reference image quality assessment H Zhu, L Li, J Wu, W Dong, G Shi Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2020 | 189 | 2020 |
| Image restoration via simultaneous sparse coding: Where structured sparsity meets gaussian scale mixture W Dong, G Shi, Y Ma, X Li International Journal of Computer Vision 114, 217-232, 2015 | 186 | 2015 |
| Nonlocal back-projection for adaptive image enlargement W Dong, L Zhang, G Shi, X Wu 2009 16th IEEE International Conference on Image Processing (ICIP), 349-352, 2009 | 185 | 2009 |
| Enhanced just noticeable difference model for images with pattern complexity J Wu, L Li, W Dong, G Shi, W Lin, CCJ Kuo IEEE Transactions on Image Processing 26 (6), 2682-2693, 2017 | 135 | 2017 |
| Mixed noise removal via Laplacian scale mixture modeling and nonlocal low-rank approximation T Huang, W Dong, X Xie, G Shi, X Bai IEEE Transactions on Image Processing 26 (7), 3171-3186, 2017 | 129 | 2017 |
| End-to-end blind image quality prediction with cascaded deep neural network J Wu, J Ma, F Liang, W Dong, G Shi, W Lin IEEE Transactions on image processing 29, 7414-7426, 2020 | 116 | 2020 |
| Image reconstruction with locally adaptive sparsity and nonlocal robust regularization W Dong, G Shi, X Li, L Zhang, X Wu Signal Processing: Image Communication 27 (10), 1109-1122, 2012 | 96 | 2012 |
| Image caption generation with part of speech guidance X He, B Shi, X Bai, GS Xia, Z Zhang, W Dong Pattern Recognition Letters 119, 229-237, 2019 | 77 | 2019 |
| Deep spatial–spectral representation learning for hyperspectral image denoising W Dong, H Wang, F Wu, G Shi, X Li IEEE Transactions on Computational Imaging 5 (4), 635-648, 2019 | 72 | 2019 |
| Low-rank tensor approximation with laplacian scale mixture modeling for multiframe image denoising W Dong, G Li, G Shi, X Li, Y Ma Proceedings of the IEEE International Conference on Computer Vision, 442-449, 2015 | 70 | 2015 |
