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default_conv

Syntologyentry name in harvested coderead from the graph 2026-09-24

default_conv appears in the code Syntology harvested for 70 papers, as 13 distinct code bodies found in 70 places (a place is one code body under one paper). At least one of them ran in 61 of the papers; 0 of the code bodies carry a behaviour fingerprint.

What this page is not. Routines are grouped here by the exact string of their function or class name. Nothing asserts that two samples named default_conv do the same thing, share code, or are comparable; the name is a string, not an identity. Behaviour outputs (what a fingerprinted sample returned on the shared battery) are not in this export and are not shown here; the graph at syntology.ai holds them. "Ran" means executed on a synthesized fixture, not that the code is correct or reproduces a paper.

Samples Syntology

Syntology ran 6 of the 13 distinct code bodies named default_conv; 7 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
5ran · our draft was wrong
0ran · fixture could not drive it
1ran
7unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 16 of the 70 places are pointer only (Syntology does not serve that copy's text). This site shows no code text for any sample; every row below links to the file in its repository where the record names one.

“Ran” means the sample executed on a synthesized input; it does not mean the output is correct. “Honoured” and “violated” refer to a contract Syntology drafted from the code itself; “our draft was wrong” and “fixture could not drive it” are failures of Syntology's instrument, not of the code, and those samples did run. The ran count above is every status except unverified, the same rule as each paper page.

Papers

70 papers shown of 70, newest first; 70 places in the table. A paper with no recorded date is placed by the month its arXiv id encodes, shown in the Date column as YYYY-MM (from id). One row per place: a paper whose repository defines the name more than once appears more than once, and the same code body held for several papers appears once under each, with the same status. Titles and dates are the archive's archive 2025-07-28 for papers in the archive, and the graph's for 2 papers added by Syntology; 13 papers have no page here and are shown by arXiv id only. Status and fingerprint are Syntology's record of each code body; licence is recorded for each place. The File cell ends with the code body's code_sha256, Syntology's identity for that exact code: an agent fetches the stored sample with Syntology's MCP tool get_code(code_sha256="…") (how to connect); click an identity to copy that call.

PaperDateFileStatus SyntologyLicence
SFedHIFI: Fire Rate-Based Heterogeneous Information Fusion for Spiking Federated Learning added by Syntology 2026-03 (from id) rtao499/SFedHIFI/model/common.py 0cba89f3cbd6fd59 unverified no licence file found · pointer only
After the Party: Navigating the Mapping From Color to Ambient Lighting added by Syntology 2025-08 (from id) fvasluianu97/RLN2/basicsr/models/archs/cc36_arch.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
arXiv:2506.22710 2025-06 (from id) MJ-NCEPU/LightBSR/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
Self-supervision via Controlled Transformation and Unpaired Self-conditioning for Low-light Image Enhancement 1 Mar 2025 aupendu/SelfEnNet/model/SelfEnNet.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Deep Variational Bayesian Modeling of Haze Degradation Process 4 Dec 2024 eunwooim/variational-dehazing-networks/GCANet/networks/FFANet.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Underwater Image Enhancement with Cascaded Contrastive Learning 16 Nov 2024 lewis081/ccl-net/models/CCLNet/Public/net/FAB.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
Degradation Oriented and Regularized Network for Blind Depth Super-Resolution 15 Oct 2024 yanzq95/dornet/net/dornet.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
Accelerating Image Super-Resolution Networks with Pixel-Level Classification 31 Jul 2024 3587jjh/PCSR/models/utils.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
HyperSIGMA: Hyperspectral Intelligence Comprehension Foundation Model 17 Jun 2024 whu-sigma/hypersigma/ImageSuperResolution/models/HyperSIGMA/model.py c559b42f16db3172 ran · our draft was wrong Apache-2.0 (permissive)
Explore Internal and External Similarity for Single Image Deraining with Graph Neural Networks 2 Jun 2024 supersupercong/msgnn/msgnn/config/graph/common.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
IRSRMamba: Infrared Image Super-Resolution via Mamba-based Wavelet Transform Feature Modulation Model 16 May 2024 yongsongh/irsrmamba/analysis/model_zoo/rcan.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
CDFormer:When Degradation Prediction Embraces Diffusion Model for Blind Image Super-Resolution 13 May 2024 identical code first harvested elsewhere 8b0e794d4d8f9b13 ran · our draft was wrong licence of this copy not recorded
Latent Modulated Function for Computational Optimal Continuous Image Representation 25 Apr 2024 hezongyao/lmf/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
Training Transformer Models by Wavelet Losses Improves Quantitative and Visual Performance in Single Image Super-Resolution 17 Apr 2024 mandalinadagi/wavelettention/wavelettention/archs/wavelettention_arch.py 1da66073b47c5596 ran · our draft was wrong Apache-2.0 (permissive)
MoCha-Stereo: Motif Channel Attention Network for Stereo Matching 10 Apr 2024 zyangchen/mocha-stereo/MoCha-Stereo/nets/refinement.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Rethinking Diffusion Model for Multi-Contrast MRI Super-Resolution 7 Apr 2024 guangyuankk/diffmsr/DiffMSR_Main/archs/common.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
Learning A Physical-aware Diffusion Model Based on Transformer for Underwater Image Enhancement 3 Mar 2024 chenydong/pa-diff/model/ddpm_trans_modules/PPU.py 7e1f7c581619b800 ran · our draft was wrong Apache-2.0 (permissive)
Adaptive Convolutional Neural Network for Image Super-resolution 24 Feb 2024 hellloxiaotian/adsrnet/HDSRNet/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
Pan-Mamba: Effective pan-sharpening with State Space Model 19 Feb 2024 alexhe101/pan-mamba/pan-sharpening/model/CDC.py c121fed8178cca17 ran no licence file found · pointer only
Kernel Diffusion: An Alternate Approach to Blind Deconvolution 4 Dec 2023 sanghviyashiitb/kernel-diff/models/deep_weiner/common.py 7e1f7c581619b800 ran · our draft was wrong MIT (permissive)
Reti-Diff: Illumination Degradation Image Restoration with Retinex-based Latent Diffusion Model 20 Nov 2023 chunminghe/reti-diff/Reti-Diff/archs/common.py 8b0e794d4d8f9b13 ran · our draft was wrong no licence file found · pointer only
Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction 29 Oct 2023 dengzeshuai/srtta/src/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:2310.17911 2023-10 (from id) hyperspectral-skin/Hyper-Skin-2023/hsiData/models/reconstruction/HDNet.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Neural Degradation Representation Learning for All-In-One Image Restoration 19 Oct 2023 mdyao/NDR-Restore/models/modules/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Towards Real-World Burst Image Super-Resolution: Benchmark and Method 9 Sep 2023 yjsunnn/fbanet/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Toward Sufficient Spatial-Frequency Interaction for Gradient-aware Underwater Image Enhancement 8 Sep 2023 zhihefang/SFGNet/SFGnet.py 7e1f7c581619b800 ran · our draft was wrong no licence file found · pointer only
DPF: Learning Dense Prediction Fields with Weak Supervision 29 Mar 2023 identical code first harvested elsewhere 7e1f7c581619b800 ran · our draft was wrong licence of this copy not recorded
Efficient and Explicit Modelling of Image Hierarchies for Image Restoration 1 Mar 2023 ofsoundof/GRL-Image-Restoration/models/common/common_edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
OSRT: Omnidirectional Image Super-Resolution with Distortion-aware Transformer 7 Feb 2023 fanghua-yu/osrt/odisr/archs/launet_arch.py 0e1c2934ef064fde unverified MIT (permissive)
Streaming Radiance Fields for 3D Video Synthesis 26 Oct 2022 algohunt/streamrf/render_delta.py 7e1f7c581619b800 ran · our draft was wrong BSD-2-Clause (permissive)
Single Image Super-Resolution via a Dual Interactive Implicit Neural Network 23 Oct 2022 robotic-vision-lab/dual-interactive-implicit-neural-network/src/models/components/common.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
Removing Batch Normalization Boosts Adversarial Training 4 Jul 2022 amazon-research/normalizer-free-robust-training/deepaug/EDSR_Model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
Demystifying the Adversarial Robustness of Random Transformation Defenses 18 Jun 2022 wagner-group/demystify-random-transform/adv/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Deep Generalized Unfolding Networks for Image Restoration 28 Apr 2022 mc-e/deep-generalized-unfolding-networks-for-image-restoration/Compressive-Sensing/DGUNet.py 1da66073b47c5596 ran · our draft was wrong no licence file found · pointer only
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment 18 Apr 2022 algolzw/bsrt/code/real/bsrt/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Neural Data-Dependent Transform for Learned Image Compression 9 Mar 2022 dezhao-wang/neural-syntax-code/model/net.py f7b46e83381fed48 ran · our draft was wrong no licence file found · pointer only
Adaptive Cross-Layer Attention for Image Restoration 4 Mar 2022 sdl-asu/acla/SR/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Learning Cross-Video Neural Representations for High-Quality Frame Interpolation 28 Feb 2022 wustl-cig/CURE/models/FENet.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Modeling Mask Uncertainty in Hyperspectral Image Reconstruction 31 Dec 2021 identical code first harvested elsewhere 8b0e794d4d8f9b13 ran · our draft was wrong licence of this copy not recorded
Local Texture Estimator for Implicit Representation Function 17 Nov 2021 jaewon-lee-b/lte/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong BSD-3-Clause (permissive)
Vector-quantized Image Modeling with Improved VQGAN 9 Oct 2021 CuddleSabe/VQGAN/VQGAN/archs/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Transformer for Single Image Super-Resolution 25 Aug 2021 luissen/esrt/model/common.py 6a89bdb621ad4a99 unverified MIT (permissive)
Unsupervised Degradation Representation Learning for Blind Super-Resolution 1 Apr 2021 LongguangWang/DASR/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Face Super-Resolution Guided by 3D Facial Priors 18 Jul 2020 HUuxiaobin/Face-Super-Resolution-Guided-by-3D-Facial-Priors/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Pyramid Attention Networks for Image Restoration 28 Apr 2020 SHI-Labs/Pyramid-Attention-Networks/CAR/code/model/common.py 1da66073b47c5596 ran · our draft was wrong MIT (permissive)
Learning A Single Network for Scale-Arbitrary Super-Resolution 8 Apr 2020 LongguangWang/ArbSR/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression 19 Mar 2020 ofsoundof/group_sparsity/model/common.py d80e2c9a3e33d17a unverified MIT (permissive)
Closed-loop Matters: Dual Regression Networks for Single Image Super-Resolution 16 Mar 2020 guoyongcs/DRN/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Zooming Slow-Mo: Fast and Accurate One-Stage Space-Time Video Super-Resolution 26 Feb 2020 YapengTian/TDAN-VSR-CVPR-2020/model.py 632c987c9fa2059e unverified MIT (permissive)
Deformable Non-local Network for Video Super-Resolution 24 Sep 2019 wh1h/DNLN/src/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Learning Filter Basis for Convolutional Neural Network Compression 23 Aug 2019 ofsoundof/learning_filter_basis/image_classification/model/common.py 0cba89f3cbd6fd59 unverified MIT (permissive)
Densely Residual Laplacian Super-Resolution 28 Jun 2019 saeed-anwar/DRLN/TestCode/code/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Feedback Network for Image Super-Resolution 23 Mar 2019 Paper99/SRFBN_CVPR19/networks/edsr_arch.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Image Super-Resolution Using Very Deep Residual Channel Attention Networks 8 Jul 2018 coloquinte/torchsr/torchsr/models/rcan.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Neural Ordinary Differential Equations 19 Jun 2018 HolmesShuan/OISR-PyTorch/NTIRE2019/OISR/src/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong BSD-2-Clause (permissive)
Maintaining Natural Image Statistics with the Contextual Loss 13 Mar 2018 subeeshvasu/2018_subeesh_epsr_eccvw/EPSR_testcode/code/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Deep Back-Projection Networks For Super-Resolution 7 Mar 2018 LEEPEIQIN/EDSR/src/model/common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
Enhanced Deep Residual Networks for Single Image Super-Resolution 10 Jul 2017 identical code first harvested elsewhere 8b0e794d4d8f9b13 ran · our draft was wrong licence of this copy not recorded
Deep Multi-scale Convolutional Neural Network for Dynamic Scene Deblurring 7 Dec 2016 SeungjunNah/DeepDeblur-PyTorch/src/model/common.py 37a49bceb7355edb unverified MIT (permissive)
arXiv:aaai_28395 yanzq95/SGNet/models/common.py 8b0e794d4d8f9b13 ran · our draft was wrong Apache-2.0 (permissive)
arXiv:aaai_28350 Baixuzx7/DISPNet/modules.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:aaai_25369 nana01219/GeoDSR/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:Zhong_Blur_Interpolation_Transformer_for_Real-World_Motion_From_Blur_CVPR_2023_paper zzh-tech/BiT/model/arches.py 2419767aa3d317ab unverified MIT (permissive)
arXiv:Xiao_Towards_Progressive_Multi-Frequency_Representation_for_Image_Warping_CVPR_2024_paper junxiao01/MFR/models/common.py 8b0e794d4d8f9b13 ran · our draft was wrong BSD-3-Clause (permissive)
arXiv:Wang_ISP2HRNet_Learning_to_Reconstruct_High_Resolution_Image_from_Irregularly_Sampled_ICCV_2025_paper yuanlinwang/ISP2HRNet/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:Wang_Deep_Adaptive_Unfolded_Network_via_Spatial_Morphology_Stripping_and_Spectral_ICCV_2025_paper Baixuzx7/DAPNet/code/modules.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:Pak_B-Spline_Texture_Coefficients_Estimator_for_Screen_Content_Image_Super-Resolution_CVPR_2023_paper ByeongHyunPak/btc/models/modules/EDSR.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)
arXiv:Han_ABCD_Arbitrary_Bitwise_Coefficient_for_De-Quantization_CVPR_2023_paper WooKyoungHan/ABCD/models/edsr.py 8b0e794d4d8f9b13 ran · our draft was wrong BSD-3-Clause (permissive)
arXiv:Deng_LAU-Net_Latitude_Adaptive_Upscaling_Network_for_Omnidirectional_Image_Super-Resolution_CVPR_2021_paper wangh-allen/LAU-Net/model/common.py 0e1c2934ef064fde unverified Apache-2.0 (permissive)
arXiv:136670429 viengiaan/EDWL/NETWORK/Demosaiced_RNAN_common.py 8b0e794d4d8f9b13 ran · our draft was wrong MIT (permissive)

This site shows no code text; each File cell links to the file on GitHub at the repository's current default branch, which may have changed since the harvest. "Pointer only" means Syntology does not serve that copy's text, for one of four reasons: no licence file was found; the licence was not identified; the licence is recorded as permissive but that copy's record is not marked cleared; or the licence is outside the permissive list Syntology serves text under (MIT, Apache-2.0, BSD and similar). Some licences outside that list permit redistribution, such as WTFPL, and GPL-3.0 under its conditions; they are simply not on the list. Hover a licence cell for the reason. Per-sample records for a paper are on its paper page under "Code Syntology ran".

Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections