| Image compressed sensing using convolutional neural network W Shi, F Jiang, S Liu, D Zhao IEEE Transactions on Image Processing 29, 375-388, 2019 | 300 | 2019 |
| Deep networks for compressed image sensing W Shi, F Jiang, S Zhang, D Zhao 2017 IEEE International Conference on Multimedia and Expo (ICME), 877-882, 2017 | 171 | 2017 |
| Scalable convolutional neural network for image compressed sensing W Shi, F Jiang, S Liu, D Zhao Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 148 | 2019 |
| Single image super-resolution with dilated convolution based multi-scale information learning inception module W Shi, F Jiang, D Zhao 2017 IEEE International Conference on Image Processing (ICIP), 977-981, 2017 | 89 | 2017 |
| Video compressed sensing using a convolutional neural network W Shi, S Liu, F Jiang, D Zhao IEEE Transactions on Circuits and Systems for Video Technology 31 (2), 425-438, 2020 | 47 | 2020 |
| VINet: A visually interpretable image diagnosis network D Gu, Y Li, F Jiang, Z Wen, S Liu, W Shi, G Lu, C Zhou IEEE Transactions on Multimedia 22 (7), 1720-1729, 2020 | 34 | 2020 |
| Hierarchical residual learning for image denoising W Shi, F Jiang, S Zhang, R Wang, D Zhao, H Zhou Signal Processing: Image Communication 76, 243-251, 2019 | 28 | 2019 |
| Visual tracking based on distribution fields and online weighted multiple instance learning J Ning, W Shi, S Yang, P Yanne Image and Vision Computing 31 (11), 853-863, 2013 | 24 | 2013 |
| A weighted full-reference image quality assessment based on visual saliency Y Wen, Y Li, X Zhang, W Shi, L Wang, J Chen Journal of Visual Communication and Image Representation 43, 119-126, 2017 | 20 | 2017 |
| Multi-scale deep networks for image compressed sensing W Shi, F Jiang, S Liu, D Zhao 2018 25th IEEE International Conference on Image Processing (ICIP), 46-50, 2018 | 19 | 2018 |
| Group-based sparse representation for low lighting image enhancement W Shi, C Chen, F Jiang, D Zhao, W Shen 2016 IEEE International Conference on Image Processing (ICIP), 4082-4086, 2016 | 15 | 2016 |
| Structure-aware deep networks and pixel-level generative adversarial training for single image super-resolution W Shi, F Tao, Y Wen IEEE Transactions on Instrumentation and Measurement 72, 1-14, 2023 | 14 | 2023 |
| Multilevel wavelet-based hierarchical networks for image compressed sensing Z Yin, WZ Shi, Z Wu, J Zhang Pattern Recognition 129, 108758, 2022 | 14 | 2022 |
| Anchored neighborhood deep network for single-image super-resolution W Shi, S Liu, F Jiang, D Zhao, Z Tian EURASIP Journal on Image and Video Processing 2018, 1-12, 2018 | 12 | 2018 |
| Entropy guided adversarial model for weakly supervised object localization SN Benassou, W Shi, F Jiang Neurocomputing 429, 60-68, 2021 | 9 | 2021 |
| Scalable convolutional neural network for image compressed sensing. In 2019 IEEE W Shi, F Jiang, S Liu, D Zhao CVF Conference on Computer Vision and Pattern Recognition (CVPR), 12282-12291, 2019 | 9 | 2019 |
| Spatial and temporal pyramid-based real-time gesture recognition F Jiang, J Ren, C Lee, W Shi, S Liu, D Zhao Journal of Real-Time Image Processing 13, 599-611, 2017 | 9 | 2017 |
| Hiding message using a cycle generative adversarial network W Shi, S Liu ACM Transactions on Multimedia Computing, Communications and Applications 18 …, 2022 | 7 | 2022 |
| Image entropy of primitive and visual quality assessment W Shi, F Jiang, D Zhao 2016 IEEE International Conference on Image Processing (ICIP), 2087-2091, 2016 | 7 | 2016 |
| Improved appearance updating method in multiple instance learning tracking J Ning, W Shi, S Yang, P Yanne IET Computer Vision 8 (2), 118-130, 2014 | 5 | 2014 |
