{"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/forecast-mae-self-supervised-pre-training-for","title":"Forecast-MAE: Self-supervised Pre-training for Motion Forecasting with Masked Autoencoders","arxiv_id":"2308.09882","date":"2023-08-19","proceeding":"ICCV 2023 1","authors":["Jie Cheng","Xiaodong Mei","Ming Liu"],"abstract":"This study explores the application of self-supervised learning (SSL) to the task of motion forecasting, an area that has not yet been extensively investigated despite the widespread success of SSL in computer vision and natural language processing. To address this gap, we introduce Forecast-MAE, an extension of the mask autoencoders framework that is specifically designed for self-supervised learning of the motion forecasting task. Our approach includes a novel masking strategy that leverages the strong interconnections between agents' trajectories and road networks, involving complementary masking of agents' future or history trajectories and random masking of lane segments. Our experiments on the challenging Argoverse 2 motion forecasting benchmark show that Forecast-MAE, which utilizes standard Transformer blocks with minimal inductive bias, achieves competitive performance compared to state-of-the-art methods that rely on supervised learning and sophisticated designs. Moreover, it outperforms the previous self-supervised learning method by a significant margin. Code is available at https://github.com/jchengai/forecast-mae.","url_abs":"https://arxiv.org/abs/2308.09882v1","url_pdf":"https://arxiv.org/pdf/2308.09882v1.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":"forecast-mae-self-supervised-pre-training-for","repo_url":"https://github.com/jchengai/forecast-mae","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"forecast-mae-self-supervised-pre-training-for","repo_url":"https://github.com/daeheepark/t4p","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[{"task_slug":"inductive-bias","task_name":"Inductive Bias"},{"task_slug":"motion-forecasting","task_name":"Motion Forecasting"},{"task_slug":"self-supervised-learning","task_name":"Self-Supervised Learning"}],"methods":[{"method_slug":"absolute-position-encodings","method_name":"Absolute Position Encodings"},{"method_slug":"adam","method_name":"Adam"},{"method_slug":"attention","method_name":"Attention"},{"method_slug":"bpe","method_name":"BPE"},{"method_slug":"dense-connections","method_name":"Dense Connections"},{"method_slug":"dropout","method_name":"Dropout"},{"method_slug":"label-smoothing","method_name":"Label Smoothing"},{"method_slug":"layer-normalization","method_name":"Layer Normalization"},{"method_slug":"linear-layer","method_name":"Linear Layer"},{"method_slug":"multi-head-attention","method_name":"Multi-Head Attention"},{"method_slug":"position-wise-feed-forward-layer","method_name":"Position-Wise Feed-Forward Layer"},{"method_slug":"residual-connection","method_name":"Residual Connection"},{"method_slug":"softmax","method_name":"Softmax"},{"method_slug":"transformer","method_name":"Transformer"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2308.09882","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2308.09882"}},"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/jchengai/forecast-mae","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/daeheepark/t4p","reach":{"status":"ok"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/AutoVision-cloud/SSL-Lanes","reach":{"status":"ok","spdx":"GPL-3.0"}}],"summary":{"ran":4,"ran_draft_wrong":1,"unverified":1},"by_repo_kind":{"official":{"samples":5,"ran":5,"repositories":1},"found_in_text":{"samples":1,"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":6,"samples":[{"code_sha256_prefix":"6c88185829ce2526","entry":"collate_fn","repo":"jchengai/forecast-mae","repo_kind":"official","path":"src/datamodule/av2_dataset.py","file_url":"https://github.com/jchengai/forecast-mae/blob/HEAD/src/datamodule/av2_dataset.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"6c88185829ce2526"}},{"code_sha256_prefix":"ebeaa065e482d4a1","entry":"get_polyline_arc_length","repo":"jchengai/forecast-mae","repo_kind":"official","path":"src/utils/vis_mae.py","file_url":"https://github.com/jchengai/forecast-mae/blob/HEAD/src/utils/vis_mae.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"ebeaa065e482d4a1"}},{"code_sha256_prefix":"182d08e88668bb2a","entry":"glob_files","repo":"jchengai/forecast-mae","repo_kind":"official","path":"preprocess.py","file_url":"https://github.com/jchengai/forecast-mae/blob/HEAD/preprocess.py","link_basis":"harvester_set","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"182d08e88668bb2a"}},{"code_sha256_prefix":"0942196a2a9acfaf","entry":"interpolate_centerline","repo":"jchengai/forecast-mae","repo_kind":"official","path":"src/utils/vis_mae.py","file_url":"https://github.com/jchengai/forecast-mae/blob/HEAD/src/utils/vis_mae.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"0942196a2a9acfaf"}},{"code_sha256_prefix":"392c09b0ae9d3bcf","entry":"interpolate_lane","repo":"jchengai/forecast-mae","repo_kind":"official","path":"src/utils/vis_mae.py","file_url":"https://github.com/jchengai/forecast-mae/blob/HEAD/src/utils/vis_mae.py","link_basis":"first_harvest_node","language":"python","status":"ran","verification_level":1,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":true,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"392c09b0ae9d3bcf"}},{"code_sha256_prefix":"4eb250143a0cd351","entry":"AttributeMask","repo":"AutoVision-cloud/SSL-Lanes","repo_kind":"found_in_text","path":"ssl_pretext_tasks/lane_masking/final_task_masking/lanegcn.py","file_url":"https://github.com/AutoVision-cloud/SSL-Lanes/blob/HEAD/ssl_pretext_tasks/lane_masking/final_task_masking/lanegcn.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"GPL-3.0","inline_ok":false,"mcp_get_code":{"code_sha256":"4eb250143a0cd351"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}