{"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/mt-orl-multi-task-occlusion-relationship","title":"MT-ORL: Multi-Task Occlusion Relationship Learning","arxiv_id":"2108.05722","date":"2021-08-12","proceeding":"ICCV 2021 10","authors":["Panhe Feng","Qi She","Lei Zhu","Jiaxin Li","Lin Zhang","Zijian Feng","Changhu Wang","Chunpeng Li","Xuejing Kang","Anlong Ming"],"abstract":"Retrieving occlusion relation among objects in a single image is challenging due to sparsity of boundaries in image. We observe two key issues in existing works: firstly, lack of an architecture which can exploit the limited amount of coupling in the decoder stage between the two subtasks, namely occlusion boundary extraction and occlusion orientation prediction, and secondly, improper representation of occlusion orientation. In this paper, we propose a novel architecture called Occlusion-shared and Path-separated Network (OPNet), which solves the first issue by exploiting rich occlusion cues in shared high-level features and structured spatial information in task-specific low-level features. We then design a simple but effective orthogonal occlusion representation (OOR) to tackle the second issue. Our method surpasses the state-of-the-art methods by 6.1%/8.3% Boundary-AP and 6.5%/10% Orientation-AP on standard PIOD/BSDS ownership datasets. Code is available at https://github.com/fengpanhe/MT-ORL.","url_abs":"https://arxiv.org/abs/2108.05722v2","url_pdf":"https://arxiv.org/pdf/2108.05722v2.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":"mt-orl-multi-task-occlusion-relationship","repo_url":"https://github.com/fengpanhe/mt-orl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"decoder","task_name":"Decoder"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2108.05722","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2108.05722"}},"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":"deterministic:regex_extraction","url":"https://github.com/fengpanhe/MT-ORL","reach":null}],"summary":{"ran":6,"ran_draft_wrong":2,"ran_fixture":1,"unverified":3},"by_repo_kind":{"official":{"samples":11,"ran":8,"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":1,"samples":[{"code_sha256_prefix":"7d84d60f38fb0d41","entry":"BasicBlock","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"7d84d60f38fb0d41"}},{"code_sha256_prefix":"4599862b7af845ff","entry":"BasicDecoder","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4599862b7af845ff"}},{"code_sha256_prefix":"393cb9bed080f6d1","entry":"ConvBnRelu","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"393cb9bed080f6d1"}},{"code_sha256_prefix":"4b06e193d47a0bfe","entry":"ResNet","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"4b06e193d47a0bfe"}},{"code_sha256_prefix":"d5cd7ffe2dc51b21","entry":"conv1x1","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"d5cd7ffe2dc51b21"}},{"code_sha256_prefix":"1907f2ae25449f39","entry":"conv3x3","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"1907f2ae25449f39"}},{"code_sha256_prefix":"e46e7885a2f69495","entry":"crop","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e46e7885a2f69495"}},{"code_sha256_prefix":"f3e25256bbd3d5b9","entry":"opm","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f3e25256bbd3d5b9"}},{"code_sha256_prefix":"e41bfdefe9e57601","entry":"osm","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"e41bfdefe9e57601"}},{"code_sha256_prefix":"f38bd74e313761e2","entry":"Bottleneck","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"f38bd74e313761e2"}},{"code_sha256_prefix":"8748c711a5242771","entry":"OPNet","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"8748c711a5242771"}},{"code_sha256_prefix":"a9f9489bc35bba93","entry":"resnet","repo":"fengpanhe/MT-ORL","repo_kind":"official","path":"mtorl/models/opnet.py","file_url":"https://github.com/fengpanhe/MT-ORL/blob/HEAD/mtorl/models/opnet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a9f9489bc35bba93"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}