{"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/any-point-trajectory-modeling-for-policy","title":"Any-point Trajectory Modeling for Policy Learning","arxiv_id":"2401.00025","date":"2023-12-28","proceeding":null,"authors":["Chuan Wen","Xingyu Lin","John So","Kai Chen","Qi Dou","Yang Gao","Pieter Abbeel"],"abstract":"Learning from demonstration is a powerful method for teaching robots new skills, and having more demonstration data often improves policy learning. However, the high cost of collecting demonstration data is a significant bottleneck. Videos, as a rich data source, contain knowledge of behaviors, physics, and semantics, but extracting control-specific information from them is challenging due to the lack of action labels. In this work, we introduce a novel framework, Any-point Trajectory Modeling (ATM), that utilizes video demonstrations by pre-training a trajectory model to predict future trajectories of arbitrary points within a video frame. Once trained, these trajectories provide detailed control guidance, enabling the learning of robust visuomotor policies with minimal action-labeled data. Across over 130 language-conditioned tasks we evaluated in both simulation and the real world, ATM outperforms strong video pre-training baselines by 80% on average. Furthermore, we show effective transfer learning of manipulation skills from human videos and videos from a different robot morphology. Visualizations and code are available at: \\url{https://xingyu-lin.github.io/atm}.","url_abs":"https://arxiv.org/abs/2401.00025v3","url_pdf":"https://arxiv.org/pdf/2401.00025v3.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":"any-point-trajectory-modeling-for-policy","repo_url":"https://github.com/large-trajectory-model/atm","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"trajectory-modeling","task_name":"Trajectory Modeling"},{"task_slug":"transfer-learning","task_name":"Transfer Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2401.00025","atlas_url":"https://app.syntology.ai/?focus=2401.00025","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2401.00025"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+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/large-trajectory-model/atm","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"ran_violates":2,"ran":2},"by_repo_kind":{"listed":{"samples":4,"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":0,"samples":[{"code_sha256_prefix":"60fff7c3c400d7ff","entry":"default","repo":"large-trajectory-model/atm","repo_kind":"listed","path":"atm/model/transformer.py","file_url":"https://github.com/large-trajectory-model/atm/blob/HEAD/atm/model/transformer.py","link_basis":"harvester_set","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"well_formed","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"60fff7c3c400d7ff"}},{"code_sha256_prefix":"aa5486a3650902d8","entry":"exists","repo":"large-trajectory-model/atm","repo_kind":"listed","path":"atm/model/transformer.py","file_url":"https://github.com/large-trajectory-model/atm/blob/HEAD/atm/model/transformer.py","link_basis":"harvester_set","language":"python","status":"ran_violates","verification_level":1,"contract_check":"VIOLATES","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"aa5486a3650902d8"}},{"code_sha256_prefix":"f17d490bddd940c0","entry":"get_dataloader","repo":"large-trajectory-model/atm","repo_kind":"listed","path":"atm/dataloader/utils.py","file_url":"https://github.com/large-trajectory-model/atm/blob/HEAD/atm/dataloader/utils.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":true,"mcp_get_code":{"code_sha256":"f17d490bddd940c0"}},{"code_sha256_prefix":"c5300df0312a38c1","entry":"load_rgb","repo":"large-trajectory-model/atm","repo_kind":"listed","path":"atm/dataloader/utils.py","file_url":"https://github.com/large-trajectory-model/atm/blob/HEAD/atm/dataloader/utils.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":true,"mcp_get_code":{"code_sha256":"c5300df0312a38c1"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}