{"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/gather-feature","entry":"gather_feature","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":5,"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":2,"n_samples_fingerprinted":0,"n_places":5,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":1,"ran_fixture":0,"ran":1,"unverified":0},"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":"2605.25127","paper":"/paper/arxiv-2605-25127","title":"PQDT: Pseudo-Query Dual Transformer for Robust Point Cloud Restoration","date":null,"month_inferred_from_arxiv_id":"2026-05","title_source":"syntology","repo":"ins-uni-bonn/PQDT","path":"pqdt/models/pq_transformer.py","file_url":"https://github.com/ins-uni-bonn/PQDT/blob/HEAD/pqdt/models/pq_transformer.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"ea0a90477e1295d3","mcp_get_code":{"code_sha256":"ea0a90477e1295d3"}},{"arxiv_id":"2307.14786","paper":"/paper/towards-deeply-unified-depth-aware-panoptic","title":"Towards Deeply Unified Depth-aware Panoptic Segmentation with Bi-directional Guidance Learning","date":"2023-07-27","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jwh97nn/DeepDPS","path":"model/utils.py","file_url":"https://github.com/jwh97nn/DeepDPS/blob/HEAD/model/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"e7fc07c30373e482","mcp_get_code":{"code_sha256":"e7fc07c30373e482"}},{"arxiv_id":"2303.05938","paper":"/paper/acr-attention-collaboration-based-regressor","title":"ACR: Attention Collaboration-based Regressor for Arbitrary Two-Hand Reconstruction","date":"2023-03-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhengdiyu/arbitrary-hands-3d-reconstruction","path":"acr/result_parser.py","file_url":"https://github.com/zhengdiyu/arbitrary-hands-3d-reconstruction/blob/HEAD/acr/result_parser.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"e7fc07c30373e482","mcp_get_code":{"code_sha256":"e7fc07c30373e482"}},{"arxiv_id":"2206.00468","paper":"/paper/panopticdepth-a-unified-framework-for-depth","title":"PanopticDepth: A Unified Framework for Depth-aware Panoptic Segmentation","date":"2022-06-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"NaiyuGao/PanopticDepth","path":"projects/PanopticDepth/panoptic_depth/utils.py","file_url":"https://github.com/NaiyuGao/PanopticDepth/blob/HEAD/projects/PanopticDepth/panoptic_depth/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"e7fc07c30373e482","mcp_get_code":{"code_sha256":"e7fc07c30373e482"}},{"arxiv_id":"2108.07682","paper":"/paper/fully-convolutional-networks-for-panoptic-1","title":"Fully Convolutional Networks for Panoptic Segmentation with Point-based Supervision","date":"2021-08-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"dvlab-research/panopticfcn","path":"panopticfcn/utils.py","file_url":"https://github.com/dvlab-research/panopticfcn/blob/HEAD/panopticfcn/utils.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"e7fc07c30373e482","mcp_get_code":{"code_sha256":"e7fc07c30373e482"}}]}