Methods › Computer Vision › Image Model Blocks › PnP › Papers, page 2
PnP
Papers archive 2025-07-28
archive papers tagged: 114 · with a code link: 43 · where Syntology ran a sample: 13 (11 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument) Syntology
Show: all tagged papersonly where code ran (13 of 114 tagged: 11 with a run with no instrument failure, 2 where every run was a failure of Syntology's instrument)
Page 2 of 2: papers 101 to 114 of 114, newest first by the archive's date (ties by slug), in archive order.
Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code, as “N ran (of which C constructed an object rather than computing a result; K with no instrument failure: H honoured, V violated, P with no contract checked; I where Syntology's instrument failed) · U unverified”; the instrument figure counts failures of Syntology's instrument, not of the code. It is per sample and not a correctness claim. When the archive marks a repository official for the paper, the line starts with that repository's state (the archive's flag, not a verdict on who wrote the code; “community repositories only” when every sample that ran came from a community repository, “official: no sample here; runs from other or unrecorded repositories” when some came from a repository the paper names or has in its text, or from none recorded); hover it for the repositories the samples that ran came from.
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ZebraPose: Coarse to Fine Surface Encoding for 6DoF Object Pose Estimation 17 Mar 2022 · 1 repository · arXiv:2203.09418Syntology official (archive's flag): 6 ran · 6 ran (of which 0 constructed an object rather than computing a result; 5 with no instrument failure: 0 honoured, 0 violated, 5 with no contract checked; 1 where Syntology's instrument failed) · 9 unverified (of 15 harvested samples)
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Newton-PnP: Real-time Visual Navigation for Autonomous Toy-Drones 5 Mar 2022 · 0 repositories · arXiv:2203.02686
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To what extent can Plug-and-Play methods outperform neural networks alone in low-dose CT reconstruction 15 Feb 2022 · 0 repositories · arXiv:2202.07173
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Bregman Plug-and-Play Priors 4 Feb 2022 · 0 repositories · arXiv:2202.02388
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Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularization 31 Jan 2022 · 1 repository · arXiv:2201.13256Syntology official (archive's flag): 7 ran · 7 ran (of which 0 constructed an object rather than computing a result; 7 with no instrument failure: 0 honoured, 0 violated, 7 with no contract checked; 0 where Syntology's instrument failed) · 2 unverified (of 9 harvested samples)
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On Maximum-a-Posteriori estimation with Plug & Play priors and stochastic gradient descent 16 Jan 2022 · 0 repositories · arXiv:2201.06133
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Adaptive Deep PnP Algorithm for Video Snapshot Compressive Imaging 14 Jan 2022 · 1 repository · arXiv:2201.05483
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It Has Potential: Gradient-Driven Denoisers for Convergent Solutions to Inverse Problems 1 Dec 2021 · 0 repositories
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Learning Eye-in-Hand Camera Calibration from a Single Image 1 Nov 2021 · 0 repositories · arXiv:2111.01245
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Learning Lipschitz-Controlled Activation Functions in Neural Networks for Plug-and-Play Image Reconstruction Methods 19 Oct 2021 · 0 repositories
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Matching Plug-and-Play Algorithms to the Denoiser 19 Oct 2021 · 0 repositories
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MRI Recovery with A Self-calibrated Denoiser 18 Oct 2021 · 0 repositories · arXiv:2110.09418
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Revisit Dictionary Learning for Video Compressive Sensing under the Plug-and-Play Framework 11 Oct 2021 · 0 repositories · arXiv:2110.04966
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PnP-DETR: Towards Efficient Visual Analysis with Transformers 15 Sep 2021 · 1 repository · arXiv:2109.07036Syntology official (archive's flag): 1 ran · 1 ran (of which 1 constructed an object rather than computing a result; 1 with no instrument failure: 0 honoured, 0 violated, 1 with no contract checked; 0 where Syntology's instrument failed) · 0 unverified; the one sample that ran constructed an object rather than computing a result (of 1 harvested sample)