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read_pfm

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

read_pfm appears in the code Syntology harvested for 24 papers, as 11 distinct code bodies found in 25 places (a place is one code body under one paper). At least one of them ran in 11 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 read_pfm 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 7 of the 11 distinct code bodies named read_pfm; 4 are unverified. One tile per status, in the site's fixed vocabulary, each code body counted once:

0ran · honoured contract
0ran · violated contract
1ran · our draft was wrong
0ran · fixture could not drive it
6ran
4unverified
0fingerprinted

Licence is a property of each copy, so it is counted per place: 2 of the 25 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

24 papers shown of 24, newest first; 25 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; 5 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
MonoMVSNet: Monocular Priors Guided Multi-View Stereo Network 15 Jul 2025 JianfeiJ/MonoMVSNet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
Towards Foundation Models for 3D Vision: How Close Are We? 14 Oct 2024 princeton-vl/uniqa-3d/Human_Study/relative_depth/utils.py b7b4d1f83d4d65fd ran BSD-3-Clause (permissive)
Self-Distilled Depth Refinement with Noisy Poisson Fusion 26 Sep 2024 lijia7/sddr/previous_evaluate_mid21.py e8a81b58ad0c60f6 ran no licence file found · pointer only
Surface-Centric Modeling for High-Fidelity Generalizable Neural Surface Reconstruction 5 Sep 2024 prstrive/SuRF/datasets/dtu_finetune.py 18ed79bdb5f6cf13 ran MIT (permissive)
GenS: Generalizable Neural Surface Reconstruction from Multi-View Images 4 Jun 2024 prstrive/gens/datasets/bmvs_finetune.py 18ed79bdb5f6cf13 ran MIT (permissive)
MVSGaussian: Fast Generalizable Gaussian Splatting Reconstruction from Multi-View Stereo 20 May 2024 TQTQliu/MVSGaussian/fusion.py 18ed79bdb5f6cf13 ran MIT (permissive)
Sharp-NeRF: Grid-based Fast Deblurring Neural Radiance Fields Using Sharpness Prior 1 Jan 2024 benhenryl/sharpnerf/preprocess_depth.py 3a47b5cabba2c155 ran MIT (permissive)
RoboDepth: Robust Out-of-Distribution Depth Estimation under Corruptions 23 Oct 2023 isl-org/DPT/util/io.py 188a19865f88f383 ran MIT (permissive)
When Epipolar Constraint Meets Non-local Operators in Multi-View Stereo 29 Sep 2023 tqtqliu/et-mvsnet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation 5 Jan 2022 prstrive/unimvsnet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
IterMVS: Iterative Probability Estimation for Efficient Multi-View Stereo 9 Dec 2021 fangjinhuawang/itermvs/datasets/data_io.py a6eab5c6529011a5 ran MIT (permissive)
AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network 9 Aug 2021 qt-zhu/aa-rmvsnet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions 27 Apr 2021 zhenpeiyang/MVS2D/patchmatch_fusion.py 1b4028697eac1b3b unverified MIT (permissive)
NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections 5 Aug 2020 kwea123/nerf_pl/datasets/depth_utils.py 6b687b02c05fe850 unverified MIT (permissive)
Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching 13 Dec 2019 alibaba/cascade-stereo/CasMVSNet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer 2 Jul 2019 anlok/depthmap-loktev/utils.py 188a19865f88f383 ran MIT (permissive)
SelFlow: Self-Supervised Learning of Optical Flow 19 Apr 2019 ppliuboy/SelFlow/flowlib.py f8c75b69f9e7a932 unverified MIT (permissive)
DDFlow: Learning Optical Flow with Unlabeled Data Distillation 25 Feb 2019 ppliuboy/DDFlow/flowlib.py f8c75b69f9e7a932 unverified MIT (permissive)
AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles 15 May 2017 Cosys-Lab/Cosys-AirSim/PythonClient/cosysairsim/pfm.py 70f08af895298f94 ran · our draft was wrong licence not identified · pointer only
arXiv:aaai_25330 susuwj/EPNet/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
arXiv:Zhang_GeoMVSNet_Learning_Multi-View_Stereo_With_Geometry_Perception_CVPR_2023_paper doubleZ0108/GeoMVSNet/fusions/dtu/_open3d.py 6b687b02c05fe850 unverified Apache-2.0 (permissive)
arXiv:Zhang_GeoMVSNet_Learning_Multi-View_Stereo_With_Geometry_Perception_CVPR_2023_paper doubleZ0108/GeoMVSNet/datasets/data_io.py b150f19350fbcd98 unverified Apache-2.0 (permissive)
arXiv:Wang_IterMVS_Iterative_Probability_Estimation_for_Efficient_Multi-View_Stereo_CVPR_2022_paper FangjinhuaWang/IterMVS/datasets/data_io.py a6eab5c6529011a5 ran MIT (permissive)
arXiv:Mi_Generalized_Binary_Search_Network_for_Highly-Efficient_Multi-View_Stereo_CVPR_2022_paper MiZhenxing/GBi-Net/datasets/data_io.py 6b687b02c05fe850 unverified MIT (permissive)
arXiv:Ding_TransMVSNet_Global_Context-Aware_Multi-View_Stereo_Network_With_Transformers_CVPR_2022_paper MegviiRobot/TransMVSNet/datasets/data_io.py 6b687b02c05fe850 unverified 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