dlut-dimt's repositories
Realworld-Underwater-Image-Enhancement-RUIE-Benchmark
Paper “Real-world Underwater Enhancement: Challenging, Benchmark and Efficient Solutions” https://arxiv.org/abs/1901.05320
LineMatching
Line matching code of ECCV2016
Two-Layer-GPR-Dehazing
The source code of Two-layer Gaussian Process Regression with Example Selection for Image Dehazing, TCSVT
TGDOF
# TGDOF This is the testing code of TGDOF for CS-MRI. Running the script "AddPath" and then the "Demo_TGDOF" to test the basic deep framework for CS-MRI. TestData ------------ The testing MR slices used in experiments, including 25 T1-weighted data and 25 T2-weighted data. The slices are extracted from the subset of the IXI datasets: http://brain-development.org/ixi-dataset/ ArtifactsModel ------------ The pre-trained model used in Module \mathcal{N}. SamplingPatter: ------------ The three kinds of sampling patterns at five different sampling ratios (10% to 50%). If you utilize this code, please cite the related paper: <br> @inproceedings{liu2019theoretically,<br> title={A theoretically guaranteed deep optimization framework for robust compressive sensing mri},<br> author={Liu, Risheng and Zhang, Yuxi and Cheng, Shichao and Fan, Xin and Luo, Zhongxuan},<br> booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},<br> volume={33},<br> pages={4368--4375},<br> year={2019} }
DPE-Deep-Prior-Ensemble
The source code of paper “Learning Converged Propagations with Deep Prior Ensemble for Image Enhancement”
Shape-to-gradient-regression
An implementation of Shape-to-gradient regression in "Explicit Shape Regression with Characteristic Number for Facial Landmark Localization "
FLDA-QR-and-IFLDA-QR
It is the code of "Fast Online Incremental Learning on Mixture Streaming Data"
Sample-of-DUT-Multi-view
20 samples from DUT Multi view dataset
TMM-3D-Face-Reconstruction
Dual Neural Networks Coupling Data Regression with Explicit Priors for Monocular 3D Face Reconstruction