{"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":"/paper/drg-dual-relation-graph-for-human-object","title":"DRG: Dual Relation Graph for Human-Object Interaction Detection","arxiv_id":"2008.11714","date":"2020-08-26","proceeding":"ECCV 2020 8","authors":["Chen Gao","Jiarui Xu","Yuliang Zou","Jia-Bin Huang"],"abstract":"We tackle the challenging problem of human-object interaction (HOI) detection. Existing methods either recognize the interaction of each human-object pair in isolation or perform joint inference based on complex appearance-based features. In this paper, we leverage an abstract spatial-semantic representation to describe each human-object pair and aggregate the contextual information of the scene via a dual relation graph (one human-centric and one object-centric). Our proposed dual relation graph effectively captures discriminative cues from the scene to resolve ambiguity from local predictions. Our model is conceptually simple and leads to favorable results compared to the state-of-the-art HOI detection algorithms on two large-scale benchmark datasets.","url_abs":"https://arxiv.org/abs/2008.11714v1","url_pdf":"https://arxiv.org/pdf/2008.11714v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"drg-dual-relation-graph-for-human-object","repo_url":"https://github.com/vt-vl-lab/DRG","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"human-object-interaction-detection","task_name":"Human-Object Interaction Detection"},{"task_slug":"object","task_name":"Object"},{"task_slug":null,"task_name":"Relation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/human-object-interaction-detection-on-hico","task":"Human-Object Interaction Detection","dataset":"HICO-DET","model":"DRG","rank_in_archive_order":36,"of":55,"metrics":{"mAP":"24.53"},"uses_additional_data":false},{"leaderboard":"/sota/human-object-interaction-detection-on-v-coco","task":"Human-Object Interaction Detection","dataset":"V-COCO","model":"DRG","rank_in_archive_order":27,"of":34,"metrics":{"AP(S1)":"51.0"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2008.11714","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.11714"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/vt-vl-lab/DRG","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran":2,"unverified":1},"by_repo_kind":{"official":{"samples":3,"ran":2,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":2,"samples":[{"code_sha256_prefix":"c42eaa8eb1b704cd","entry":"sigmoid_focal_loss_cpu","repo":"vt-vl-lab/DRG","repo_kind":"official","path":"maskrcnn_benchmark/layers/sigmoid_focal_loss.py","file_url":"https://github.com/vt-vl-lab/DRG/blob/HEAD/maskrcnn_benchmark/layers/sigmoid_focal_loss.py","link_basis":"plan_row","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"c42eaa8eb1b704cd"}},{"code_sha256_prefix":"e261fa29066b37e5","entry":"smooth_l1_loss","repo":"vt-vl-lab/DRG","repo_kind":"official","path":"maskrcnn_benchmark/layers/smooth_l1_loss.py","file_url":"https://github.com/vt-vl-lab/DRG/blob/HEAD/maskrcnn_benchmark/layers/smooth_l1_loss.py","link_basis":"harvester_set","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"mcp_get_code":{"code_sha256":"e261fa29066b37e5"}},{"code_sha256_prefix":"2902bf4410253ff7","entry":"interpolate","repo":"vt-vl-lab/DRG","repo_kind":"official","path":"maskrcnn_benchmark/layers/misc.py","file_url":"https://github.com/vt-vl-lab/DRG/blob/HEAD/maskrcnn_benchmark/layers/misc.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":false,"mcp_get_code":{"code_sha256":"2902bf4410253ff7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}