{"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/radius-gaussian","entry":"radius_gaussian","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":11,"n_papers_ran":8,"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":5,"n_samples_ran":2,"n_samples_fingerprinted":1,"n_places":11,"n_places_pointer_only":4,"by_status":{"ran_honours":0,"ran_violates":1,"ran_draft_wrong":1,"ran_fixture":0,"ran":0,"unverified":3},"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":"2410.03644","paper":"/paper/unlearnable-3d-point-clouds-class-wise","title":"Unlearnable 3D Point Clouds: Class-wise Transformation Is All You Need","date":"2024-10-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"CGCL-codes/UnlearnablePC","path":"model_utils/kpconv_util.py","file_url":"https://github.com/CGCL-codes/UnlearnablePC/blob/HEAD/model_utils/kpconv_util.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2308.05525","paper":"/paper/critical-points-an-agile-point-cloud","title":"Robustifying Point Cloud Networks by Refocusing","date":"2023-08-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yossilevii100/critical_points2","path":"shape_invariant_attack/model_utils/kpconv_util.py","file_url":"https://github.com/yossilevii100/critical_points2/blob/HEAD/shape_invariant_attack/model_utils/kpconv_util.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2308.04782","paper":"/paper/pointmbf-a-multi-scale-bidirectional-fusion","title":"PointMBF: A Multi-scale Bidirectional Fusion Network for Unsupervised RGB-D Point Cloud Registration","date":"2023-08-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"phdymz/pointmbf","path":"models/block.py","file_url":"https://github.com/phdymz/pointmbf/blob/HEAD/models/block.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2301.10222","paper":"/paper/rangevit-towards-vision-transformers-for-3d","title":"RangeViT: Towards Vision Transformers for 3D Semantic Segmentation in Autonomous Driving","date":"2023-01-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"valeoai/rangevit","path":"models/rangevit.py","file_url":"https://github.com/valeoai/rangevit/blob/HEAD/models/rangevit.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2203.04041","paper":"/paper/shape-invariant-3d-adversarial-point-clouds","title":"Shape-invariant 3D Adversarial Point Clouds","date":"2022-03-08","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shikiw/SI-Adv","path":"model_utils/kpconv_util.py","file_url":"https://github.com/shikiw/SI-Adv/blob/HEAD/model_utils/kpconv_util.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2111.12591","paper":"/paper/lepard-learning-partial-point-cloud-matching","title":"Lepard: Learning partial point cloud matching in rigid and deformable scenes","date":"2021-11-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"rabbityl/lepard","path":"models/blocks.py","file_url":"https://github.com/rabbityl/lepard/blob/HEAD/models/blocks.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2007.12668","paper":"/paper/kprnet-improving-projection-based-lidar","title":"KPRNet: Improving projection-based LiDAR semantic segmentation","date":"2020-07-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"DeyvidKochanov-TomTom/kprnet","path":"models/kpconv/blocks.py","file_url":"https://github.com/DeyvidKochanov-TomTom/kprnet/blob/HEAD/models/kpconv/blocks.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"42f2cd40ba483d3b","mcp_get_code":{"code_sha256":"42f2cd40ba483d3b"}},{"arxiv_id":"2007.06888","paper":"/paper/jsenet-joint-semantic-segmentation-and-edge","title":"JSENet: Joint Semantic Segmentation and Edge Detection Network for 3D Point Clouds","date":"2020-07-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hzykent/JSENet","path":"JSENet_code/kernels/convolution_ops.py","file_url":"https://github.com/hzykent/JSENet/blob/HEAD/JSENet_code/kernels/convolution_ops.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b211e6b58ff40f29","mcp_get_code":{"code_sha256":"b211e6b58ff40f29"}},{"arxiv_id":"2007.01294","paper":"/paper/a-closer-look-at-local-aggregation-operators","title":"A Closer Look at Local Aggregation Operators in Point Cloud Analysis","date":"2020-07-02","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zeliu98/CloserLook3D","path":"pytorch/models/utlis.py","file_url":"https://github.com/zeliu98/CloserLook3D/blob/HEAD/pytorch/models/utlis.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"code_sha256_prefix":"7140c9e040fc1297","mcp_get_code":{"code_sha256":"7140c9e040fc1297"}},{"arxiv_id":"1904.08889","paper":"/paper/kpconv-flexible-and-deformable-convolution","title":"KPConv: Flexible and Deformable Convolution for Point Clouds","date":"2019-04-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"isl-org/Open3D-ML","path":"ml3d/torch/models/kpconv.py","file_url":"https://github.com/isl-org/Open3D-ML/blob/HEAD/ml3d/torch/models/kpconv.py","status":"ran_draft_wrong","verification_level":1,"contract_check":"MISDECLARED","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"c0186f8ddb0bc115","mcp_get_code":{"code_sha256":"c0186f8ddb0bc115"}},{"arxiv_id":"Ao_BUFFER_Balancing_Accuracy_Efficiency_and_Generalizability_in_Point_Cloud_Registration_CVPR_2023_paper","paper":null,"title":"arXiv:Ao_BUFFER_Balancing_Accuracy_Efficiency_and_Generalizability_in_Point_Cloud_Registration_CVPR_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"aosheng1996/BUFFER","path":"models/point_learner.py","file_url":"https://github.com/aosheng1996/BUFFER/blob/HEAD/models/point_learner.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"7829aba7b104b42a","mcp_get_code":{"code_sha256":"7829aba7b104b42a"}}]}