Zhang, Z.H.[Zhong-Hao],
Liu, Y.P.[Yi-Peng],
Liu, J.[Jiani],
Wen, F.[Fei],
Zhu, C.[Ce],
AMP-Net: Denoising-Based Deep Unfolding for Compressive Image Sensing,
IP(30), 2021, pp. 1487-1500.
IEEE DOI
2101
Image reconstruction, Noise reduction, Sparse matrices,
Iterative algorithms, Visualization, Optimization, Neural networks,
image reconstruction
BibRef
Meng, Z.Y.[Zi-Yi],
Yuan, X.[Xin],
Jalali, S.[Shirin],
Deep Unfolding for Snapshot Compressive Imaging,
IJCV(131), No. 1, January 2023, pp. 2933-2958.
Springer DOI
2310
BibRef
Yang, X.[Xin],
Yang, C.L.[Chun-Ling],
MAP-Inspired Deep Unfolding Network for Distributed Compressive Video
Sensing,
SPLetters(30), 2023, pp. 309-313.
IEEE DOI
2304
Image reconstruction, Correlation, Optical imaging, Adaptive optics,
Optical signal processing, Iterative methods, multi-hypothesis
BibRef
Song, J.C.[Jie-Chong],
Chen, B.[Bin],
Zhang, J.[Jian],
Dynamic Path-Controllable Deep Unfolding Network for Compressive
Sensing,
IP(32), 2023, pp. 2202-2214.
IEEE DOI
2305
Heuristic algorithms, Optimization, Image reconstruction,
Image coding, Compressed sensing, Image restoration, dynamic modulation
BibRef
Song, J.C.[Jie-Chong],
Chen, B.[Bin],
Zhang, J.[Jian],
Deep Memory-Augmented Proximal Unrolling Network for Compressive
Sensing,
IJCV(131), No. 6, June 2023, pp. 1477-1496.
Springer DOI
2305
BibRef
Ye, D.J.[Dong-Jie],
Ni, Z.K.[Zhang-Kai],
Wang, H.[Hanli],
Zhang, J.[Jian],
Wang, S.Q.[Shi-Qi],
Kwong, S.[Sam],
CSformer: Bridging Convolution and Transformer for Compressive Sensing,
IP(32), 2023, pp. 2827-2842.
IEEE DOI
2306
Transformers, Image reconstruction, Convolutional neural networks,
Convolution, Deep learning, image reconstruction
BibRef
Cui, W.X.[Wen-Xue],
Fan, X.P.[Xiao-Peng],
Zhang, J.[Jian],
Zhao, D.B.[De-Bin],
Deep Unfolding Network for Image Compressed Sensing by
Content-Adaptive Gradient Updating and Deformation-Invariant
Non-Local Modeling,
MultMed(26), 2024, pp. 4012-4027.
IEEE DOI
2402
Image reconstruction, Compressed sensing, Adaptation models, Deformable models,
Image coding, Adaptive systems, Limiting, proximal gradient descent (PGD)
BibRef
Li, W.Q.[Wei-Qi],
Chen, B.[Bin],
Liu, S.[Shuai],
Zhao, S.J.[Shi-Jie],
Du, B.[Bowen],
Zhang, Y.B.[Yong-Bing],
Zhang, J.[Jian],
D3C2-Net: Dual-Domain Deep Convolutional Coding Network for
Compressive Sensing,
CirSysVideo(34), No. 10, October 2024, pp. 9341-9355.
IEEE DOI Code:
WWW Link.
2411
Convolutional codes, Convolution, Optimization, Encoding,
Artificial neural networks, Image reconstruction, Image coding,
deep unfolding network
BibRef
Wang, L.[Luhua],
Zhang, J.[Jun],
BPDQ_p-Net: A Deep Unfolding Method for Quantized Compressed Sensing,
SPLetters(31), 2024, pp. 531-535.
IEEE DOI
2402
Quantization (signal), Distortion, Signal reconstruction,
Signal processing algorithms, Compressed sensing, Transforms,
quantized measurements
BibRef
Guo, Z.[Zhen],
Gan, H.P.[Hong-Ping],
USB-Net: Unfolding Split Bregman Method With Multi-Phase Feature
Integration for Compressive Imaging,
IP(34), 2025, pp. 925-938.
IEEE DOI
2502
Image reconstruction, Optimization, Feature extraction, Image coding,
Iterative algorithms, Convergence, multi-phase feature integration
BibRef
Guo, Z.[Zhen],
Gan, H.P.[Hong-Ping],
CPP-Net: Embracing Multi-Scale Feature Fusion into Deep Unfolding
CP-PPA Network for Compressive Sensing,
CVPR24(25086-25095)
IEEE DOI Code:
WWW Link.
2410
Deep learning, Superresolution, Feature extraction,
Distortion, Iterative methods, Image reconstruction,
Deep Unfolding Networks
BibRef
Alhejaili, R.[Rawwad],
Alfarraj, M.[Motaz],
Al-Shaikhi, A.[Ali],
Listen to your gradients: Integrating gradients into deep unfolding
networks,
PRL(192), 2025, pp. 99-105.
Elsevier DOI
2505
Compressed sensing, Deep unfolding networks,
Proximal gradient descent deep unfolding networks,
Deep compressed sensing networks
BibRef
Wu, H.B.[Hong-Bing],
Huang, S.Y.[Si-Yang],
Guo, X.J.[Xiao-Jun],
Sun, X.Y.[Xiao-Yong],
Sun, B.[Bei],
Zhang, Z.[Zhuo],
Su, S.J.[Shao-Jing],
FWS-Net: Fixed-Point Deep Unfolding Network for compressed sensing
via multi-scale wavelet fusion and state-space modeling,
CVIU(265), 2026, pp. 104630.
Elsevier DOI
2603
Compressed sensing, Deep Unfolding Network, FPC,
State space model, Wavelet fusion
BibRef
Liao, C.[Chen],
Shen, Y.[Yan],
Wang, Z.L.[Zhong-Li],
Li, Y.B.[Yan-Bing],
Adaptive Use of Convex or Non-Convex Optimization in Deep Unfolding
Network for Image Compressive Sensing,
MultMed(28), 2026, pp. 2850-2864.
IEEE DOI
2604
Optimization, Convex functions, Measurement, Image reconstruction,
Neural networks, Hands, Symmetric matrices, Iterative algorithms, non-convex
BibRef
Guo, Z.[Zhen],
Gan, H.P.[Hong-Ping],
Degradation-Aware Unfolding Network With Sparsity-Gated Experts,
IP(35), 2026, pp. 10987-11001.
IEEE DOI
2610
Modeling, Degradation, PSNR, Compressed sensing, Visualization, Dams,
Routing, Magnetic resonance imaging, Optimization, Measurement,
degradation-aware
BibRef
Xu, P.[Ping],
Liu, L.[Lei],
Zheng, H.F.[Hai-Feng],
Yuan, X.[Xin],
Xu, C.[Chen],
Xue, L.Y.[Ling-Yun],
Degradation-Aware Dynamic Fourier-Based Network for Spectral
Compressive Imaging,
MultMed(26), 2024, pp. 2838-2850.
IEEE DOI
2402
Image reconstruction, Degradation, Feature extraction, Imaging,
Mathematical models, Heuristic algorithms, Convolution,
snapshot compressive imaging
BibRef
Liu, L.[Lei],
Xu, P.[Ping],
Yuan, X.[Xin],
Xu, C.[Chen],
Zheng, H.F.[Hai-Feng],
Degradation learning adaptive deep unfolding network for spectral
compressive imaging,
PR(175), 2026, pp. 113058.
Elsevier DOI
2603
Snapshot compressive imaging, Deep learning, Hyperspectral images
BibRef
Yin, J.F.[Jian-Fu],
Tao, C.L.[Cheng-Long],
Hu, B.L.[Bing-Liang],
Wang, Y.[Yao],
Wang, Q.[Quan],
An efficient deep unfolding approach for snapshot compressed imaging
of motion videos,
PR(179), 2026, pp. 113554.
Elsevier DOI Code:
WWW Link.
2606
Snapshot compressive imaging, Deep unfolding,
Degradation estimation, Denoising
BibRef
Zhou, Z.[Zheng],
Lai, J.T.[Jin-Tao],
Yang, X.F.[Xiao-Fei],
Cao, Z.[Zhong],
Yang, W.[Wenbiao],
Shang, W.L.[Wen-Li],
3DMAUNet: A 3D Memory-Augmented Deep Unfolding Network with Dynamic
Momentum Updating for Snapshot Compressive Spectral Imaging,
RS(18), No. 20, 2026, pp. 3471.
DOI Link
2610
BibRef
Shen, F.Y.[Fei-Yang],
Gan, H.P.[Hong-Ping],
HUNet: Homotopy Unfolding Network for Image Compressive Sensing,
CVPR25(12799-12808)
IEEE DOI Code:
WWW Link.
2508
Representation learning, Source coding, Face recognition,
Feature extraction, Transformers, Propagation losses,
feature fusion
BibRef
Liao, C.[Chen],
Shen, Y.[Yan],
Li, D.[Dan],
Wang, Z.L.[Zhong-Li],
Using Powerful Prior Knowledge of Diffusion Model in Deep Unfolding
Networks for Image Compressive Sensing,
CVPR25(18000-18010)
IEEE DOI Code:
WWW Link.
2508
Knowledge engineering, Scalability, Neural networks,
Diffusion models, Approximation algorithms, Solids, DMP-DUN
BibRef
Zhang, J.C.[Jian-Cheng],
Zeng, H.J.[Hai-Jin],
Cao, J.[Jiezhang],
Chen, Y.Y.[Yong-Yong],
Yu, D.X.[Deng-Xiu],
Zhao, Y.P.[Yin-Ping],
Dual Prior Unfolding for Snapshot Compressive Imaging,
CVPR24(25742-25752)
IEEE DOI Code:
WWW Link.
2410
Degradation, Image coding, Costs, Noise reduction, Imaging,
Iterative methods, image restoration
BibRef
Dong, Y.[Yubo],
Gao, D.[Dahua],
Qiu, T.[Tian],
Li, Y.Y.[Yu-Yan],
Yang, M.X.[Min-Xi],
Shi, G.M.[Guang-Ming],
Residual Degradation Learning Unfolding Framework with Mixing Priors
Across Spectral and Spatial for Compressive Spectral Imaging,
CVPR23(22262-22271)
IEEE DOI
2309
BibRef
Zhao, L.J.[Li-Jun],
Wang, K.[Ke],
Zhang, J.J.[Jin-Jing],
Zhao, J.[Jie],
Wang, A.H.[An-Hong],
A Joint Model-Driven Unfolding Network for Degraded Low-Quality
Color-Depth Images Enhancement,
ICIP23(625-629)
IEEE DOI
2312
BibRef
Jin, M.Y.[Meng-Ying],
Wei, Z.H.[Zhi-Hui],
Xiao, L.[Liang],
Learning Texture Enhancement Prior with Deep Unfolding Network for
Snapshot Compressive Imaging,
ACCV22(III:357-373).
Springer DOI
2307
BibRef
Wu, Z.L.[Zong-Liang],
Lu, R.Y.[Rui-Ying],
Fu, Y.[Ying],
Yuan, X.[Xin],
Latent Diffusion Prior Enhanced Deep Unfolding for Snapshot Spectral
Compressive Imaging,
ECCV24(XXXIII: 164-181).
Springer DOI
2412
BibRef
Yang, C.S.[Cheng-Shuai],
Zhang, S.Y.[Shi-Yu],
Yuan, X.[Xin],
Ensemble Learning Priors Driven Deep Unfolding for Scalable Video
Snapshot Compressive Imaging,
ECCV22(XXIII:600-618).
Springer DOI
2211
BibRef
Wt, Z.Y.[Zhuo-Yuan],
Zhangt, J.[Jian],
Mou, C.[Chong],
Dense Deep Unfolding Network with 3D-CNN Prior for Snapshot
Compressive Imaging,
ICCV21(4872-4881)
IEEE DOI
2203
Adaptation models, Correlation, Codes, Computational modeling,
Buildings, Low-level and physics-based vision,
Optimization and learning methods
BibRef
Chapter on Image Processing, Restoration, Enhancement, Filters, Image and Video Coding continues in
Coded Aperture Compressive Sensing .