Softwares (源代码下载)

7. Proximal Dehaze-net (ECCV 2018)

Link to code: https://github.com/legendongary/. We will release the training code soon.

 

6. BM3D-Net

Link to code: https://github.com/legendongary/BM3D-Net

[1] Dong Yang, Jian Sun*. BM3D-Net: A Convolutional Neural Network for Transform-Domain Collaborative Filtering, IEEE Signal Processing Letter, 2018

 

5.  Deep ADMM-Net for Compressive Sensing MRI

Link to code: https://github.com/yangyan92/Deep-ADMM-Net

References:

[1] [ Yan Yang, Jian Sun, Huibin Li, Zongben Xu.  Deep ADMM-Net for Compressive Sensing MRIAdvances in Neural Information Processing Systems (NIPS), 2016

 

4.  Learning Dictionary of Discriminative Part Detectors for Image Categorization and Cosegmentation (code)

References:

[1]Jian Sun and Jean Ponce. Learning Dictionary of Discriminative Part Detectors for Image Categorization and CosegmentationInternational Journal of Computer Vision, accepted, 2015.

[2]Jian Sun, Jean Ponce. Learning Discriminative Part Detectors for Image Classification and CosegmentationInternational Conf. Computer Vision (ICCV), Sydney, 2013 


3. Learning a convolutional neural network for non-uniform motion blur removal (code)

Reference:

[1] Jian Sun, Wenfei Cao, Zongben Xu, Jean Ponce. Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), Columbus, USA, 2015


2. Tensor PCA for background substraction from compressive measurements (code)

Reference:

[1] Wenfei Cao, Yao Wang, Jian Sun, Deyu Meng, Can Yang, Andrzej Cichocki, Zongben Xu, A Novel Tensor Robust PCA Approach for Background Subtraction from Compressive Measurements (demo codes), IEEE Transactions on Image Processing, accepted with revision, 2015.


1. Non-local range Markov Random Field for image restoration (demo code)

 Reference:

[1]Jian Sun, Marshall Tappen. Learning Non-Local Range Markov Random Field for Image RestorationIEEE Conf. Computer Vision and Pattern Recognition (CVPR), Colorado, USA, 2011.