{"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/partial-video-domain-adaptation-with-partial","title":"Partial Video Domain Adaptation with Partial Adversarial Temporal Attentive Network","arxiv_id":"2107.04941","date":"2021-07-11","proceeding":"ICCV 2021 10","authors":["Yuecong Xu","Jianfei Yang","Haozhi Cao","Qi Li","Kezhi Mao","Zhenghua Chen"],"abstract":"Partial Domain Adaptation (PDA) is a practical and general domain adaptation scenario, which relaxes the fully shared label space assumption such that the source label space subsumes the target one. The key challenge of PDA is the issue of negative transfer caused by source-only classes. For videos, such negative transfer could be triggered by both spatial and temporal features, which leads to a more challenging Partial Video Domain Adaptation (PVDA) problem. In this paper, we propose a novel Partial Adversarial Temporal Attentive Network (PATAN) to address the PVDA problem by utilizing both spatial and temporal features for filtering source-only classes. Besides, PATAN constructs effective overall temporal features by attending to local temporal features that contribute more toward the class filtration process. We further introduce new benchmarks to facilitate research on PVDA problems, covering a wide range of PVDA scenarios. Empirical results demonstrate the state-of-the-art performance of our proposed PATAN across the multiple PVDA benchmarks.","url_abs":"https://arxiv.org/abs/2107.04941v1","url_pdf":"https://arxiv.org/pdf/2107.04941v1.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":[],"tasks":[{"task_slug":"domain-adaptation","task_name":"Domain Adaptation"},{"task_slug":"partial-domain-adaptation","task_name":"Partial Domain Adaptation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2107.04941","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2107.04941"}},"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/xuyu0010/PATAN","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_draft_wrong":1,"unverified":6},"by_repo_kind":{"found_in_text":{"samples":7,"ran":1,"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":0,"samples":[{"code_sha256_prefix":"77f89e05c55c985d","entry":"conv3x3","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/util.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/util.py","link_basis":"plan_row","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"77f89e05c55c985d"}},{"code_sha256_prefix":"b352238f535c2545","entry":"autofill","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"train_da.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/train_da.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b352238f535c2545"}},{"code_sha256_prefix":"17e56ae071fc11eb","entry":"get_config","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/config.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/config.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"17e56ae071fc11eb"}},{"code_sha256_prefix":"b698c26db8509688","entry":"get_symbol","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/symbol_builder.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/symbol_builder.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"b698c26db8509688"}},{"code_sha256_prefix":"90def75b21b5e19b","entry":"init_3d_from_2d_dict","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/initializer.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/initializer.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"90def75b21b5e19b"}},{"code_sha256_prefix":"5b1ff5687e0b6042","entry":"load_state","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/util.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/util.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5b1ff5687e0b6042"}},{"code_sha256_prefix":"d0257b12c85879e1","entry":"make_res_layer","repo":"xuyu0010/PATAN","repo_kind":"found_in_text","path":"network/util.py","file_url":"https://github.com/xuyu0010/PATAN/blob/HEAD/network/util.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d0257b12c85879e1"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}