{"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/process-model-info","entry":"process_model_info","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":21,"n_papers_ran":21,"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":5,"n_samples_fingerprinted":0,"n_places":21,"n_places_pointer_only":2,"by_status":{"ran_honours":0,"ran_violates":0,"ran_draft_wrong":0,"ran_fixture":0,"ran":5,"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":"2505.19028","paper":"/paper/infochartqa-a-benchmark-for-multimodal","title":"InfoChartQA: A Benchmark for Multimodal Question Answering on Infographic Charts","date":"2025-05-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"orionbench/orionbench","path":"model_evaluation/mmdetection/.dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/orionbench/orionbench/blob/HEAD/model_evaluation/mmdetection/.dev_scripts/convert_test_benchmark_script.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":"3175ca3b1ec8c7b9","mcp_get_code":{"code_sha256":"3175ca3b1ec8c7b9"}},{"arxiv_id":"2405.06228","paper":"/paper/context-guided-spatial-feature-reconstruction","title":"Context-Guided Spatial Feature Reconstruction for Efficient Semantic Segmentation","date":"2024-05-10","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"nizhenliang/cgrseg","path":".dev/generate_benchmark_evaluation_script.py","file_url":"https://github.com/nizhenliang/cgrseg/blob/HEAD/.dev/generate_benchmark_evaluation_script.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":"39403bf2697d1720","mcp_get_code":{"code_sha256":"39403bf2697d1720"}},{"arxiv_id":"2404.04823","paper":"/paper/3d-building-reconstruction-from-monocular-1","title":"3D Building Reconstruction from Monocular Remote Sensing Images with Multi-level Supervisions","date":"2024-04-07","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"opendatalab/MLS-BRN","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/opendatalab/MLS-BRN/blob/HEAD/.dev_scripts/convert_test_benchmark_script.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2402.00868","paper":"/paper/we-re-not-using-videos-effectively-an-updated","title":"We're Not Using Videos Effectively: An Updated Domain Adaptive Video Segmentation Baseline","date":"2024-02-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"simarkareer/unifiedvideoda","path":".dev/generate_benchmark_evaluation_script.py","file_url":"https://github.com/simarkareer/unifiedvideoda/blob/HEAD/.dev/generate_benchmark_evaluation_script.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":"8dae673faa871413","mcp_get_code":{"code_sha256":"8dae673faa871413"}},{"arxiv_id":"2401.02361","paper":"/paper/an-open-and-comprehensive-pipeline-for","title":"An Open and Comprehensive Pipeline for Unified Object Grounding and Detection","date":"2024-01-04","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"open-mmlab/mmdetection","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/open-mmlab/mmdetection/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"3175ca3b1ec8c7b9","mcp_get_code":{"code_sha256":"3175ca3b1ec8c7b9"}},{"arxiv_id":"2312.15895","paper":"/paper/semantic-aware-sam-for-point-prompted","title":"Semantic-aware SAM for Point-Prompted Instance Segmentation","date":"2023-12-26","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhaoyangwei123/sapnet","path":"TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/zhaoyangwei123/sapnet/blob/HEAD/TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"code_sha256_prefix":"eb266541a2fb6b57","mcp_get_code":{"code_sha256":"eb266541a2fb6b57"}},{"arxiv_id":"2310.05590","paper":"/paper/perceptual-artifacts-localization-for-image-1","title":"Perceptual Artifacts Localization for Image Synthesis Tasks","date":"2023-10-09","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"open-mmlab/mmsegmentation","path":".dev_scripts/generate_benchmark_evaluation_script.py","file_url":"https://github.com/open-mmlab/mmsegmentation/blob/HEAD/.dev_scripts/generate_benchmark_evaluation_script.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":"39403bf2697d1720","mcp_get_code":{"code_sha256":"39403bf2697d1720"}},{"arxiv_id":"2308.09534","paper":"/paper/small-object-detection-via-coarse-to-fine","title":"Small Object Detection via Coarse-to-fine Proposal Generation and Imitation Learning","date":"2023-08-18","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"shaunyuan22/CFINet","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/shaunyuan22/CFINet/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2303.14488","paper":"/paper/adaptive-sparse-convolutional-networks-with","title":"Adaptive Sparse Convolutional Networks with Global Context Enhancement for Faster Object Detection on Drone Images","date":"2023-03-25","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Cuogeihong/CEASC","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/Cuogeihong/CEASC/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2303.11749","paper":"/paper/detecting-everything-in-the-open-world","title":"Detecting Everything in the Open World: Towards Universal Object Detection","date":"2023-03-21","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"zhenyuw16/UniDetector","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/zhenyuw16/UniDetector/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2212.07784","paper":"/paper/rtmdet-an-empirical-study-of-designing-real","title":"RTMDet: An Empirical Study of Designing Real-Time Object Detectors","date":"2022-12-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"RangiLyu/mmdetection_test","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/RangiLyu/mmdetection_test/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"3175ca3b1ec8c7b9","mcp_get_code":{"code_sha256":"3175ca3b1ec8c7b9"}},{"arxiv_id":"2209.09841","paper":"/paper/rethinking-data-augmentation-in-knowledge","title":"Exploring Inconsistent Knowledge Distillation for Object Detection with Data Augmentation","date":"2022-09-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"jwliang007/ikd","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/jwliang007/ikd/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2207.06827","paper":"/paper/point-to-box-network-for-accurate-object","title":"Point-to-Box Network for Accurate Object Detection via Single Point Supervision","date":"2022-07-14","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ucas-vg/P2BNet","path":"TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/ucas-vg/P2BNet/blob/HEAD/TOV_mmdetection/.dev_scripts/convert_test_benchmark_script.py","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"code_sha256_prefix":"eb266541a2fb6b57","mcp_get_code":{"code_sha256":"eb266541a2fb6b57"}},{"arxiv_id":"2204.02136","paper":"/paper/overcoming-catastrophic-forgetting-in-1","title":"Overcoming Catastrophic Forgetting in Incremental Object Detection via Elastic Response Distillation","date":"2022-04-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"Hi-FT/ERD","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/Hi-FT/ERD/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"3175ca3b1ec8c7b9","mcp_get_code":{"code_sha256":"3175ca3b1ec8c7b9"}},{"arxiv_id":"2203.16527","paper":"/paper/exploring-plain-vision-transformer-backbones","title":"Exploring Plain Vision Transformer Backbones for Object Detection","date":"2022-03-30","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"ViTAE-Transformer/ViTDet","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/ViTAE-Transformer/ViTDet/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2203.10593","paper":"/paper/open-vocabulary-one-stage-detection-with","title":"Open-Vocabulary One-Stage Detection with Hierarchical Visual-Language Knowledge Distillation","date":"2022-03-20","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"mengqidyangge/hierkd","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/mengqidyangge/hierkd/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2107.00420","paper":"/paper/cbnetv2-a-composite-backbone-network","title":"CBNet: A Composite Backbone Network Architecture for Object Detection","date":"2021-07-01","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"VDIGPKU/CBNetV2","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/VDIGPKU/CBNetV2/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"2105.15203","paper":"/paper/segformer-simple-and-efficient-design-for","title":"SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers","date":"2021-05-31","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"UAws/CV-3315-Is-All-You-Need","path":".dev/generate_benchmark_evaluation_script.py","file_url":"https://github.com/UAws/CV-3315-Is-All-You-Need/blob/HEAD/.dev/generate_benchmark_evaluation_script.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":"39403bf2697d1720","mcp_get_code":{"code_sha256":"39403bf2697d1720"}},{"arxiv_id":"2105.01928","paper":"/paper/queryinst-parallelly-supervised-mask-query","title":"Instances as Queries","date":"2021-05-05","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"sty16/cell_mmdetection","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/sty16/cell_mmdetection/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"1906.07155","paper":"/paper/mmdetection-open-mmlab-detection-toolbox-and","title":"MMDetection: Open MMLab Detection Toolbox and Benchmark","date":"2019-06-17","month_inferred_from_arxiv_id":null,"title_source":"archive","repo":"fehmikahraman/mmdetection","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/fehmikahraman/mmdetection/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}},{"arxiv_id":"Zhang_Reconciling_Object-Level_and_Global-Level_Objectives_for_Long-Tail_Detection_ICCV_2023_paper","paper":null,"title":"arXiv:Zhang_Reconciling_Object-Level_and_Global-Level_Objectives_for_Long-Tail_Detection_ICCV_2023_paper","date":null,"month_inferred_from_arxiv_id":null,"title_source":null,"repo":"EricZsy/ROG","path":".dev_scripts/convert_test_benchmark_script.py","file_url":"https://github.com/EricZsy/ROG/blob/HEAD/.dev_scripts/convert_test_benchmark_script.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":"893e052530d28946","mcp_get_code":{"code_sha256":"893e052530d28946"}}]}