{"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/gaussian-2d","entry":"gaussian_2d","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":0,"n_places":11,"n_places_pointer_only":1,"by_status":{"ran_honours":0,"ran_violates":1,"ran_draft_wrong":0,"ran_fixture":0,"ran":1,"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":"2502.06756","paper":"/paper/samrefiner-taming-segment-anything-model-for","title":"SAMRefiner: Taming Segment Anything Model for Universal Mask Refinement","date":"2025-02-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"linyq2117/samrefiner","path":"SAMRefiner_plus/utils.py","file_url":"https://github.com/linyq2117/samrefiner/blob/HEAD/SAMRefiner_plus/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"a75b4ea06278636b","mcp_get_code":{"code_sha256":"a75b4ea06278636b"}},{"arxiv_id":"2501.18616","paper":"/paper/stamp-scalable-task-and-model-agnostic","title":"STAMP: Scalable Task And Model-agnostic Collaborative Perception","date":"2025-01-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"taco-group/STAMP","path":"opencood/loss/center_point_loss.py","file_url":"https://github.com/taco-group/STAMP/blob/HEAD/opencood/loss/center_point_loss.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"2406.16863","paper":"/paper/freetraj-tuning-free-trajectory-control-in","title":"FreeTraj: Tuning-Free Trajectory Control in Video Diffusion Models","date":"2024-06-24","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"arthur-qiu/freetraj","path":"lvdm/modules/attention_freetraj.py","file_url":"https://github.com/arthur-qiu/freetraj/blob/HEAD/lvdm/modules/attention_freetraj.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":"3fa8442a049bccd4","mcp_get_code":{"code_sha256":"3fa8442a049bccd4"}},{"arxiv_id":"2401.13964","paper":"/paper/an-extensible-framework-for-open","title":"An Extensible Framework for Open Heterogeneous Collaborative Perception","date":"2024-01-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"yifanlu0227/HEAL","path":"opencood/loss/center_point_loss.py","file_url":"https://github.com/yifanlu0227/HEAL/blob/HEAD/opencood/loss/center_point_loss.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"code_sha256_prefix":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"2401.00896","paper":"/paper/trailblazer-trajectory-control-for-diffusion","title":"TrailBlazer: Trajectory Control for Diffusion-Based Video Generation","date":"2023-12-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"hohonu-vicml/trailblazer","path":"TrailBlazer/CrossAttn/BaseProc.py","file_url":"https://github.com/hohonu-vicml/trailblazer/blob/HEAD/TrailBlazer/CrossAttn/BaseProc.py","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"invariant","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"650163523cd1441e","mcp_get_code":{"code_sha256":"650163523cd1441e"}},{"arxiv_id":"2303.16818","paper":"/paper/bevsimdet-simulated-multi-modal-distillation","title":"SimDistill: Simulated Multi-modal Distillation for BEV 3D Object Detection","date":"2023-03-29","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"vitae-transformer/bevsimdet","path":"mmdet3d/core/utils/gaussian.py","file_url":"https://github.com/vitae-transformer/bevsimdet/blob/HEAD/mmdet3d/core/utils/gaussian.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":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"2205.13542","paper":"/paper/bevfusion-multi-task-multi-sensor-fusion-with","title":"BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation","date":"2022-05-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mit-han-lab/bevfusion","path":"mmdet3d/core/utils/gaussian.py","file_url":"https://github.com/mit-han-lab/bevfusion/blob/HEAD/mmdet3d/core/utils/gaussian.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":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"2203.16910","paper":"/paper/end-to-end-trajectory-distribution-prediction","title":"End-to-End Trajectory Distribution Prediction Based on Occupancy Grid Maps","date":"2022-03-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Kguo-cs/TDOR","path":"model/utils.py","file_url":"https://github.com/Kguo-cs/TDOR/blob/HEAD/model/utils.py","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"b3ce0a5e8e83e340","mcp_get_code":{"code_sha256":"b3ce0a5e8e83e340"}},{"arxiv_id":"2203.10642","paper":"/paper/futr3d-a-unified-sensor-fusion-framework-for","title":"FUTR3D: A Unified Sensor Fusion Framework for 3D Detection","date":"2022-03-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"xiaohao-xu/unified-pretrain-ad","path":"mmdet3d/core/utils/gaussian.py","file_url":"https://github.com/xiaohao-xu/unified-pretrain-ad/blob/HEAD/mmdet3d/core/utils/gaussian.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"2006.11275","paper":"/paper/center-based-3d-object-detection-and-tracking","title":"Center-based 3D Object Detection and Tracking","date":"2020-06-19","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"tianweiy/CenterPoint-KITTI","path":"pcdet/models/dense_heads/centerpoint_head_single.py","file_url":"https://github.com/tianweiy/CenterPoint-KITTI/blob/HEAD/pcdet/models/dense_heads/centerpoint_head_single.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":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}},{"arxiv_id":"aaai_28577","paper":null,"title":"arXiv:aaai_28577","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"ViTAE-Transformer/SimDistill","path":"mmdet3d/core/utils/gaussian.py","file_url":"https://github.com/ViTAE-Transformer/SimDistill/blob/HEAD/mmdet3d/core/utils/gaussian.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":"ea036153b550642a","mcp_get_code":{"code_sha256":"ea036153b550642a"}}]}