{"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/fineparser-a-fine-grained-spatio-temporal","title":"FineParser: A Fine-grained Spatio-temporal Action Parser for Human-centric Action Quality Assessment","arxiv_id":"2405.06887","date":"2024-05-11","proceeding":"CVPR 2024 1","authors":["Jinglin Xu","Sibo Yin","Guohao Zhao","Zishuo Wang","Yuxin Peng"],"abstract":"Existing action quality assessment (AQA) methods mainly learn deep representations at the video level for scoring diverse actions. Due to the lack of a fine-grained understanding of actions in videos, they harshly suffer from low credibility and interpretability, thus insufficient for stringent applications, such as Olympic diving events. We argue that a fine-grained understanding of actions requires the model to perceive and parse actions in both time and space, which is also the key to the credibility and interpretability of the AQA technique. Based on this insight, we propose a new fine-grained spatial-temporal action parser named \\textbf{FineParser}. It learns human-centric foreground action representations by focusing on target action regions within each frame and exploiting their fine-grained alignments in time and space to minimize the impact of invalid backgrounds during the assessment. In addition, we construct fine-grained annotations of human-centric foreground action masks for the FineDiving dataset, called \\textbf{FineDiving-HM}. With refined annotations on diverse target action procedures, FineDiving-HM can promote the development of real-world AQA systems. Through extensive experiments, we demonstrate the effectiveness of FineParser, which outperforms state-of-the-art methods while supporting more tasks of fine-grained action understanding. Data and code are available at \\url{https://github.com/PKU-ICST-MIPL/FineParser_CVPR2024}.","url_abs":"https://arxiv.org/abs/2405.06887v1","url_pdf":"https://arxiv.org/pdf/2405.06887v1.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":"fineparser-a-fine-grained-spatio-temporal","repo_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"action-quality-assessment","task_name":"Action Quality Assessment"},{"task_slug":"action-understanding","task_name":"Action Understanding"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/action-quality-assessment-on-finediving","task":"Action Quality Assessment","dataset":"FineDiving","model":"FineParser","rank_in_archive_order":2,"of":4,"metrics":{"RL2(*100)":"0.2602","Spearman Correlation":"0.9435"},"uses_additional_data":false},{"leaderboard":"/sota/action-quality-assessment-on-mtl-aqa","task":"Action Quality Assessment","dataset":"MTL-AQA","model":"FineParser","rank_in_archive_order":5,"of":21,"metrics":{"RL2(*100)":"0.241","Spearman Correlation":"95.85"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2405.06887","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2405.06887"}},"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/pku-icst-mipl/fineparser_cvpr2024","reach":null}],"summary":{"ran":3,"ran_fixture":1,"unverified":1},"by_repo_kind":{"official":{"samples":5,"ran":4,"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":5,"samples":[{"code_sha256_prefix":"ce8f234651f6a7eb","entry":"double_conv","repo":"pku-icst-mipl/fineparser_cvpr2024","repo_kind":"official","path":"models/mask.py","file_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024/blob/HEAD/models/mask.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ce8f234651f6a7eb"}},{"code_sha256_prefix":"908e33aeb1851e04","entry":"down","repo":"pku-icst-mipl/fineparser_cvpr2024","repo_kind":"official","path":"models/mask.py","file_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024/blob/HEAD/models/mask.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"908e33aeb1851e04"}},{"code_sha256_prefix":"767fcfa0fbe650fa","entry":"inconv","repo":"pku-icst-mipl/fineparser_cvpr2024","repo_kind":"official","path":"models/mask.py","file_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024/blob/HEAD/models/mask.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"767fcfa0fbe650fa"}},{"code_sha256_prefix":"499f3b5ebc730523","entry":"seg_pool_2d","repo":"pku-icst-mipl/fineparser_cvpr2024","repo_kind":"official","path":"models/mask.py","file_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024/blob/HEAD/models/mask.py","link_basis":"first_harvest_node","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":"invariant","behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"499f3b5ebc730523"}},{"code_sha256_prefix":"32859381fb963ae3","entry":"VideoEncoder","repo":"pku-icst-mipl/fineparser_cvpr2024","repo_kind":"official","path":"models/mask.py","file_url":"https://github.com/pku-icst-mipl/fineparser_cvpr2024/blob/HEAD/models/mask.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"32859381fb963ae3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}