{"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/learning-long-term-visual-dynamics-with","title":"Learning Long-term Visual Dynamics with Region Proposal Interaction Networks","arxiv_id":"2008.02265","date":"2020-08-05","proceeding":"ICLR 2021 1","authors":["Haozhi Qi","Xiaolong Wang","Deepak Pathak","Yi Ma","Jitendra Malik"],"abstract":"Learning long-term dynamics models is the key to understanding physical common sense. Most existing approaches on learning dynamics from visual input sidestep long-term predictions by resorting to rapid re-planning with short-term models. This not only requires such models to be super accurate but also limits them only to tasks where an agent can continuously obtain feedback and take action at each step until completion. In this paper, we aim to leverage the ideas from success stories in visual recognition tasks to build object representations that can capture inter-object and object-environment interactions over a long-range. To this end, we propose Region Proposal Interaction Networks (RPIN), which reason about each object's trajectory in a latent region-proposal feature space. Thanks to the simple yet effective object representation, our approach outperforms prior methods by a significant margin both in terms of prediction quality and their ability to plan for downstream tasks, and also generalize well to novel environments. Code, pre-trained models, and more visualization results are available at https://haozhi.io/RPIN.","url_abs":"https://arxiv.org/abs/2008.02265v5","url_pdf":"https://arxiv.org/pdf/2008.02265v5.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":"learning-long-term-visual-dynamics-with","repo_url":"https://github.com/HaozhiQi/RPIN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"common-sense-reasoning","task_name":"Common Sense Reasoning"},{"task_slug":"object","task_name":"Object"},{"task_slug":"region-proposal","task_name":"Region Proposal"},{"task_slug":"visual-reasoning","task_name":"Visual Reasoning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/visual-reasoning-on-phyre-1b-cross","task":"Visual Reasoning","dataset":"PHYRE-1B-Cross","model":"RPIN","rank_in_archive_order":1,"of":4,"metrics":{"AUCCESS":"42.2"},"uses_additional_data":false},{"leaderboard":"/sota/visual-reasoning-on-phyre-1b-within","task":"Visual Reasoning","dataset":"PHYRE-1B-Within","model":"RPIN","rank_in_archive_order":1,"of":4,"metrics":{"AUCCESS":"85.2"},"uses_additional_data":false}],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2008.02265","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2008.02265"}},"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/HaozhiQi/RPIN","reach":null}],"summary":{"unverified":3},"by_repo_kind":{"official":{"samples":3,"ran":0,"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":3,"samples":[{"code_sha256_prefix":"75eee68db79557c6","entry":"InterNet","repo":"HaozhiQi/RPIN","repo_kind":"official","path":"rpin/models/rpcin.py","file_url":"https://github.com/HaozhiQi/RPIN/blob/HEAD/rpin/models/rpcin.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":"75eee68db79557c6"}},{"code_sha256_prefix":"972fc8397efba3b1","entry":"Net","repo":"HaozhiQi/RPIN","repo_kind":"official","path":"rpin/models/rpcin.py","file_url":"https://github.com/HaozhiQi/RPIN/blob/HEAD/rpin/models/rpcin.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":"972fc8397efba3b1"}},{"code_sha256_prefix":"3763a600c2f4099c","entry":"build_backbone","repo":"HaozhiQi/RPIN","repo_kind":"official","path":"rpin/models/rpcin.py","file_url":"https://github.com/HaozhiQi/RPIN/blob/HEAD/rpin/models/rpcin.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":"3763a600c2f4099c"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}