{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/code/read-gipuma-dmb","entry":"read_gipuma_dmb","source":"Syntology graph, per-sample; not an archive number","read_at":"2026-09-24T18:15:14+00:00","claim":"Names are grouped by exact entry-name string. Same-named routines are NOT asserted to be equivalent; 'ran' means executed on a synthesized fixture, not correctness. n_samples_ran = sum of by_status over every status except 'unverified' (ran_draft_wrong and ran_fixture are failures of Syntology's instrument, not of the code); n_papers_ran = papers with at least one such sample.","status_vocabulary":{"ran_honours":"ran, honoured the contract we drafted","ran_violates":"ran, violated the contract we drafted","ran_draft_wrong":"ran; our contract draft was wrong, not the code","ran_fixture":"ran; our fixture could not drive it","ran":"ran on a synthesized input","unverified":"unverified (harvested, no recorded run)"},"n_papers":6,"n_papers_ran":0,"units":"n_samples, n_samples_ran, n_samples_fingerprinted and by_status count distinct code bodies (code_sha256); n_places and n_places_pointer_only count places, one per (paper, code body) pair, which is also the unit of the samples list","n_samples":1,"n_samples_ran":0,"n_samples_fingerprinted":0,"n_places":6,"n_places_pointer_only":0,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":0,"unverified":1},"syntology":{"atlas_url":null,"mcp":null,"mcp_per_sample":{"tool":"get_code","arguments_in":"samples[].mcp_get_code"},"developers":"https://syntology.ai/developers"},"samples":[{"arxiv_id":"2201.01501","paper":"/paper/rethinking-depth-estimation-for-multi-view","title":"Rethinking Depth Estimation for Multi-View Stereo: A Unified Representation","date":"2022-01-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"prstrive/unimvsnet","path":"filter/gipuma.py","file_url":"https://github.com/prstrive/unimvsnet/blob/HEAD/filter/gipuma.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}},{"arxiv_id":"2007.10872","paper":"/paper/dense-hybrid-recurrent-multi-view-stereo-net","title":"Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking","date":"2020-07-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"haibao637/D2HC-RMVSNet","path":"mvsnet/depthfusion.py","file_url":"https://github.com/haibao637/D2HC-RMVSNet/blob/HEAD/mvsnet/depthfusion.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}},{"arxiv_id":"1912.06378","paper":"/paper/cascade-cost-volume-for-high-resolution-multi","title":"Cascade Cost Volume for High-Resolution Multi-View Stereo and Stereo Matching","date":"2019-12-13","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"alibaba/cascade-stereo","path":"CasMVSNet/gipuma.py","file_url":"https://github.com/alibaba/cascade-stereo/blob/HEAD/CasMVSNet/gipuma.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}},{"arxiv_id":"1905.02706","paper":"/paper/learning-unsupervised-multi-view-stereopsis","title":"Learning Unsupervised Multi-View Stereopsis via Robust Photometric Consistency","date":"2019-05-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tejaskhot/unsup_mvs","path":"code/unsup_mvsnet/depthfusion_dtu.py","file_url":"https://github.com/tejaskhot/unsup_mvs/blob/HEAD/code/unsup_mvsnet/depthfusion_dtu.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}},{"arxiv_id":"1902.10556","paper":"/paper/recurrent-mvsnet-for-high-resolution-multi","title":"Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inference","date":"2019-02-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"YoYo000/MVSNet","path":"mvsnet/depthfusion.py","file_url":"https://github.com/YoYo000/MVSNet/blob/HEAD/mvsnet/depthfusion.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}},{"arxiv_id":"Ding_TransMVSNet_Global_Context-Aware_Multi-View_Stereo_Network_With_Transformers_CVPR_2022_paper","paper":null,"title":"arXiv:Ding_TransMVSNet_Global_Context-Aware_Multi-View_Stereo_Network_With_Transformers_CVPR_2022_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"MegviiRobot/TransMVSNet","path":"gipuma.py","file_url":"https://github.com/MegviiRobot/TransMVSNet/blob/HEAD/gipuma.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"f6147a9b9d73ca5e","mcp_get_code":{"code_sha256":"f6147a9b9d73ca5e"}}]}