Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging | Paper Citation Record

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This paper cites Modl: Model-based deep learning architecture for inverse problems.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Modl: Model-based deep learning architecture for inverse problems

Reference 1

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This paper cites Contour detection and hierarchical image seg- mentation.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Contour detection and hierarchical image seg- mentation

Reference 2

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This paper cites A fast iterative shrinkage- thresholding algorithm for linear inverse problems.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging A fast iterative shrinkage- thresholding algorithm for linear inverse problems

Reference 3

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This paper cites Deep unfolding of a proximal interior point method for image restoration.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Deep unfolding of a proximal interior point method for image restoration

Reference 4

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This paper cites Iterative hard thresholding for compressed sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Iterative hard thresholding for compressed sensing

Reference 5

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This paper cites Caiafa and Andrzej Cichocki.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Caiafa and Andrzej Cichocki

Reference 6

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This paper cites Candes and Terence Tao.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Candes and Terence Tao

Reference 7

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This paper cites Ro- bust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Ro- bust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information

Reference 8

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This paper cites Proxi- mal splitting methods in signal processing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Proxi- mal splitting methods in signal processing

Reference 9

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This paper cites Compressive sensing via nonlocal low-rank regu- larization.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Compressive sensing via nonlocal low-rank regu- larization

Reference 10

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This paper cites Denoising prior driven deep neural network for image restoration.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Denoising prior driven deep neural network for image restoration

Reference 11

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This paper cites an unresolved cited work.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Unresolved cited work

Reference 12

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This paper cites Single-pixel imaging via compressive sampling.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Single-pixel imaging via compressive sampling

Reference 13

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This paper cites Principles and prospects for single-pixel imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Principles and prospects for single-pixel imaging

Reference 14

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This paper cites What’s in a prior? learned proximal networks for inverse problems.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging What’s in a prior? learned proximal networks for inverse problems

Reference 15

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This paper cites Gradient projection for sparse reconstruction: Ap- plication to compressed sensing and other inverse problems.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Gradient projection for sparse reconstruction: Ap- plication to compressed sensing and other inverse problems

Reference 16

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This paper cites Nonlinear image recov- ery with half-quadratic regularization.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Nonlinear image recov- ery with half-quadratic regularization

Reference 17

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This paper cites Cpp-net: Embracing multi- scale feature fusion into deep unfolding cp-ppa network for compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Cpp-net: Embracing multi- scale feature fusion into deep unfolding cp-ppa network for compressive sensing

Reference 18

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This paper cites Robust stochastically-descending unrolled net- works.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Robust stochastically-descending unrolled net- works

Reference 19

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This paper cites Single pixel imaging at megahertz switching rates via cyclic hadamard masks.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Single pixel imaging at megahertz switching rates via cyclic hadamard masks

Reference 20

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This paper cites Exploiting structure in wavelet-based bayesian compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Exploiting structure in wavelet-based bayesian compressive sensing

Reference 21

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Observation c63eea78-58be-4741-958d-eefe22e0af63 · outbound

This paper cites Stochastic Deep Restoration Priors for Imaging Inverse Problems.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Stochastic Deep Restoration Priors for Imaging Inverse Problems

Reference 22

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This paper cites Gradient step denoiser for convergent plug-and-play.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Gradient step denoiser for convergent plug-and-play

Reference 23

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This paper cites Proximal denoiser for convergent plug-and-play optimiza- tion with nonconvex regularization.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Proximal denoiser for convergent plug-and-play optimiza- tion with nonconvex regularization

Reference 24

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This paper cites Kamilov, Charles A.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Kamilov, Charles A

Reference 25

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This paper cites Com- pressed sensing using a gaussian scale mixtures model in wavelet domain.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Com- pressed sensing using a gaussian scale mixtures model in wavelet domain

Reference 26

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This paper cites Reconnet: Non-iterative reconstruc- tion of images from compressively sensed measurements.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Reconnet: Non-iterative reconstruc- tion of images from compressively sensed measurements

Reference 27

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This paper cites An efficient algorithm for compressed mr imaging using to- tal variation and wavelets.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging An efficient algorithm for compressed mr imaging using to- tal variation and wavelets

Reference 28

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This paper cites Learned d-amp: Principled neural network based compressive image recovery.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Learned d-amp: Principled neural network based compressive image recovery

Reference 29

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This paper cites From denoising to compressed sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging From denoising to compressed sensing

Reference 30

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This paper cites Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing

Reference 31

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Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Deep generalized unfolding networks for image restoration

Reference 32

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This paper cites Proximal algorithms.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Proximal algorithms

Reference 33

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This paper cites How do vision transform- ers work? In 10th International Conference on Learning Representations, ICLR 2022, 2022.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging How do vision transform- ers work? In 10th International Conference on Learning Representations, ICLR 2022, 2022

Reference 34

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This paper cites Dual-scale trans- former for large-scale single-pixel imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Dual-scale trans- former for large-scale single-pixel imaging

Reference 35

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This paper cites The little engine that could: Regularization by denoising (red).

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging The little engine that could: Regularization by denoising (red)

Reference 36

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This paper cites Plug-and-play methods provably converge with properly trained denoisers.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Plug-and-play methods provably converge with properly trained denoisers

Reference 37

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This paper cites Transcs: a transformer-based hybrid architecture for image compressed sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Transcs: a transformer-based hybrid architecture for image compressed sensing

Reference 38

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This paper cites Im- age compressed sensing using convolutional neural network.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Im- age compressed sensing using convolutional neural network

Reference 39

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This paper cites Scalable convolutional neural network for image compressed sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Scalable convolutional neural network for image compressed sensing

Reference 40

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This paper cites Memory- augmented deep unfolding network for compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Memory- augmented deep unfolding network for compressive sensing

Reference 41

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This paper cites Optimization-inspired cross-attention transformer for compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Optimization-inspired cross-attention transformer for compressive sensing

Reference 42

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This paper cites 3d computational imaging with single-pixel detectors.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging 3d computational imaging with single-pixel detectors

Reference 43

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This paper cites Block coordi- nate regularization by denoising.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Block coordi- nate regularization by denoising

Reference 44

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This paper cites Scalable plug-and-play admm with con- vergence guarantees.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Scalable plug-and-play admm with con- vergence guarantees

Reference 45

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This paper cites Plug-and-play algorithms for single-pixel imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Plug-and-play algorithms for single-pixel imaging

Reference 46

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This paper cites Saunet: Spatial-attention unfold- ing network for image compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Saunet: Spatial-attention unfold- ing network for image compressive sensing

Reference 47

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This paper cites Full- resolution and full-dynamic-range coded aperture compres- sive temporal imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Full- resolution and full-dynamic-range coded aperture compres- sive temporal imaging

Reference 48

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Observation 326fef03-b034-431b-8d58-11f9cbc01cd5 · outbound

This paper cites Deep optics for video snapshot compressive imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Deep optics for video snapshot compressive imaging

Reference 49

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This paper cites Hier- archical separable video transformer for snapshot compres- sive imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Hier- archical separable video transformer for snapshot compres- sive imaging

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:10.215888Z

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 839cbb7f-2d2d-4bef-a0a9-f6e70e449796 · outbound

This paper cites Ufc-net: Unrolling fixed-point continuous network for deep compressive sens- ing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Ufc-net: Unrolling fixed-point continuous network for deep compressive sens- ing

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:10.059562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 5ef90f4e-a300-4e65-91c8-6b79298306d9 · outbound

This paper cites Terahertz compressive imaging with metamaterial spatial light modulators.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Terahertz compressive imaging with metamaterial spatial light modulators

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:09.879066Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 86d90922-c06e-40dd-8dbd-0068050b2186 · outbound

This paper cites Alternating direction algo- rithms for ℓ1-problems in compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Alternating direction algo- rithms for ℓ1-problems in compressive sensing

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:09.683571Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 469c0cb4-39d8-4ded-b71b-24153c0ecad8 · outbound

This paper cites Admm- csnet: A deep learning approach for image compressive sens- ing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Admm- csnet: A deep learning approach for image compressive sens- ing

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:09.470618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 282bb256-7c4e-46c8-9d1a-768d3cefeb9c · outbound

This paper cites Dr2-net: Deep residual re- construction network for image compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Dr2-net: Deep residual re- construction network for image compressive sensing

Reference 55

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:09.271957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 1a64bfd5-bcdc-4d7b-b255-2e7ac5700bef · outbound

This paper cites Csformer: Bridging convolution and transformer for compressive sensing.IEEE Transactions on Image Processing, 32:2827–2842, 2023.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Csformer: Bridging convolution and transformer for compressive sensing.IEEE Transactions on Image Processing, 32:2827–2842, 2023

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:09.082983Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b9cccdfb-38d5-4fa7-b37a-c75cd7f3b31b · outbound

This paper cites Coast: Controllable arbitrary-sampling network for com- pressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Coast: Controllable arbitrary-sampling network for com- pressive sensing

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.881949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 54a8c01f-6df8-4ddd-8a10-f89d65029d00 · outbound

This paper cites Generalized alternating projection based total variation minimization for compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Generalized alternating projection based total variation minimization for compressive sensing

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.721082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation b8f6ba51-317b-4532-a276-d89fdefe610a · outbound

This paper cites Brady, and Aggelos K.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Brady, and Aggelos K

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.565359Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 8cd78a11-39e0-423b-a70b-be2fb4138389 · outbound

This paper cites Restormer: Efficient transformer for high-resolution image restoration.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Restormer: Efficient transformer for high-resolution image restoration

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.418404Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 3354a81b-10da-460e-8c59-989eceb9779b · outbound

This paper cites Ista-net: Interpretable optimization-inspired deep network for image compressive sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Ista-net: Interpretable optimization-inspired deep network for image compressive sensing

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.228120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 453de779-0e9f-4c2b-9f1d-28eff51485bb · outbound

This paper cites Optimization- inspired compact deep compressive sensing.IEEE Journal of Selected Topics in Signal Processing, 14(4):765–774, 2020.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Optimization- inspired compact deep compressive sensing.IEEE Journal of Selected Topics in Signal Processing, 14(4):765–774, 2020

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:08.091577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 237fa7eb-934b-4bff-abc8-38ca6a39a2ca · outbound

This paper cites Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Beyond a gaussian denoiser: Residual learning of deep cnn for image denoising

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:07.934310Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 718eaa29-3519-4096-bad3-aed61cb89cac · outbound

This paper cites Learning deep cnn denoiser prior for image restoration.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Learning deep cnn denoiser prior for image restoration

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-07T12:58:06.899163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abd85b70-6554-4d70-9441-fb747d6a1fe9 · outbound

This paper cites Ffdnet: Toward a fast and flexible solution for cnn-based image denoising.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Ffdnet: Toward a fast and flexible solution for cnn-based image denoising

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-07T12:58:07.023198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44f1432a-2c96-426e-b2bf-ba091a27f013 · outbound

This paper cites Plug-and-play image restora- tion with deep denoiser prior.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Plug-and-play image restora- tion with deep denoiser prior

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:07.811538Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4ab89012-a8cf-4efb-929d-b2e847fd3a83 · outbound

This paper cites Hadamard single-pixel imaging versus fourier single-pixel imaging.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Hadamard single-pixel imaging versus fourier single-pixel imaging

Reference 67

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:07.666515Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 4f30ddd6-96e5-43bb-8c72-e4530f78e023 · outbound

This paper cites Amp-net: Denoising-based deep unfolding for com- pressive image sensing.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging Amp-net: Denoising-based deep unfolding for com- pressive image sensing

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:58:07.536391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 66263c2c-bca2-406f-b183-da478ee39be6 · outbound

This paper cites 2, 3, 6, 7.

Proximal Algorithm Unrolling: Flexible and Efficient Reconstruction Networks for Single-Pixel Imaging 2, 3, 6, 7

Reference 5557

Resolution: parse uncertain; raw_fallback, observed 2026-08-07T12:58:12.444175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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