{"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/load-segmentation","entry":"load_segmentation","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":5,"n_papers_ran":4,"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":2,"n_samples_ran":1,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":3,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"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":"2404.04876","paper":"/paper/hilo-detailed-and-robust-3d-clothed-human","title":"HiLo: Detailed and Robust 3D Clothed Human Reconstruction with High-and Low-Frequency Information of Parametric Models","date":"2024-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"YifYang993/HiLo","path":"lib/common/cloth_extraction.py","file_url":"https://github.com/YifYang993/HiLo/blob/HEAD/lib/common/cloth_extraction.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3433ad17bc7e6650","mcp_get_code":{"code_sha256":"3433ad17bc7e6650"}},{"arxiv_id":"2312.06704","paper":"/paper/sifu-side-view-conditioned-implicit-function","title":"SIFU: Side-view Conditioned Implicit Function for Real-world Usable Clothed Human Reconstruction","date":"2023-12-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"River-Zhang/SIFU","path":"lib/common/cloth_extraction.py","file_url":"https://github.com/River-Zhang/SIFU/blob/HEAD/lib/common/cloth_extraction.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"3433ad17bc7e6650","mcp_get_code":{"code_sha256":"3433ad17bc7e6650"}},{"arxiv_id":"2309.13524","paper":"/paper/global-correlated-3d-decoupling-transformer-1","title":"Global-correlated 3D-decoupling Transformer for Clothed Avatar Reconstruction","date":"2023-09-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"River-Zhang/GTA","path":"lib/common/cloth_extraction.py","file_url":"https://github.com/River-Zhang/GTA/blob/HEAD/lib/common/cloth_extraction.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3433ad17bc7e6650","mcp_get_code":{"code_sha256":"3433ad17bc7e6650"}},{"arxiv_id":"2308.08857","paper":"/paper/d-if-uncertainty-aware-human-digitization-via","title":"D-IF: Uncertainty-aware Human Digitization via Implicit Distribution Field","date":"2023-08-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"psyai-net/d-if_release","path":"lib/common/cloth_extraction.py","file_url":"https://github.com/psyai-net/d-if_release/blob/HEAD/lib/common/cloth_extraction.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"3433ad17bc7e6650","mcp_get_code":{"code_sha256":"3433ad17bc7e6650"}},{"arxiv_id":"2003.14407","paper":"/paper/probabilistic-pixel-adaptive-refinement","title":"Probabilistic Pixel-Adaptive Refinement Networks","date":"2020-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"visinf/ppac_refinement","path":"src/datasets/data_utils.py","file_url":"https://github.com/visinf/ppac_refinement/blob/HEAD/src/datasets/data_utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"70b6a212163abbef","mcp_get_code":{"code_sha256":"70b6a212163abbef"}}]}