{"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/vectornet-encoding-hd-maps-and-agent-dynamics","title":"VectorNet: Encoding HD Maps and Agent Dynamics from Vectorized Representation","arxiv_id":"2005.04259","date":"2020-05-08","proceeding":"CVPR 2020 6","authors":["Jiyang Gao","Chen Sun","Hang Zhao","Yi Shen","Dragomir Anguelov","Cong-Cong Li","Cordelia Schmid"],"abstract":"Behavior prediction in dynamic, multi-agent systems is an important problem in the context of self-driving cars, due to the complex representations and interactions of road components, including moving agents (e.g. pedestrians and vehicles) and road context information (e.g. lanes, traffic lights). This paper introduces VectorNet, a hierarchical graph neural network that first exploits the spatial locality of individual road components represented by vectors and then models the high-order interactions among all components. In contrast to most recent approaches, which render trajectories of moving agents and road context information as bird-eye images and encode them with convolutional neural networks (ConvNets), our approach operates on a vector representation. By operating on the vectorized high definition (HD) maps and agent trajectories, we avoid lossy rendering and computationally intensive ConvNet encoding steps. To further boost VectorNet's capability in learning context features, we propose a novel auxiliary task to recover the randomly masked out map entities and agent trajectories based on their context. We evaluate VectorNet on our in-house behavior prediction benchmark and the recently released Argoverse forecasting dataset. Our method achieves on par or better performance than the competitive rendering approach on both benchmarks while saving over 70% of the model parameters with an order of magnitude reduction in FLOPs. It also outperforms the state of the art on the Argoverse dataset.","url_abs":"https://arxiv.org/abs/2005.04259v1","url_pdf":"https://arxiv.org/pdf/2005.04259v1.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":"vectornet-encoding-hd-maps-and-agent-dynamics","repo_url":"https://github.com/CoderHun/VectorNet_Implement","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"vectornet-encoding-hd-maps-and-agent-dynamics","repo_url":"https://github.com/DQSSSSS/VectorNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"vectornet-encoding-hd-maps-and-agent-dynamics","repo_url":"https://github.com/henry1iu/tnt-trajectory-prediction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}},{"paper_slug":"vectornet-encoding-hd-maps-and-agent-dynamics","repo_url":"https://github.com/xk-huang/yet-another-vectornet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"graph-neural-network","task_name":"Graph Neural Network"},{"task_slug":"self-driving-cars","task_name":"Self-Driving Cars"}],"methods":[{"method_slug":"graph-neural-network","method_name":"Graph Neural Network"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2005.04259","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2005.04259"}},"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/henry1iu/tnt-trajectory-prediction","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/xk-huang/yet-another-vectornet","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/DQSSSSS/VectorNet","reach":{"status":"ok"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/CoderHun/VectorNet_Implement","reach":{"status":"ok"}}],"summary":{"unverified":6},"by_repo_kind":{"listed":{"samples":6,"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":0,"samples":[{"code_sha256_prefix":"8a14e71868084022","entry":"encoding_features","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"utils/feature_utils.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/utils/feature_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"8a14e71868084022"}},{"code_sha256_prefix":"0a0b004efff199e3","entry":"get_agent_feature_ls","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"utils/agent_utils.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/utils/agent_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"0a0b004efff199e3"}},{"code_sha256_prefix":"2a3112a64bfbb3dd","entry":"get_fc_edge_index","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"dataset.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/dataset.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"2a3112a64bfbb3dd"}},{"code_sha256_prefix":"a7ec18cd5a3d41a0","entry":"get_rect_lane_id","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"utils/lane_utils.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/utils/lane_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"a7ec18cd5a3d41a0"}},{"code_sha256_prefix":"418336fe652715b1","entry":"masked_softmax","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"modeling/selfatten.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/modeling/selfatten.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"418336fe652715b1"}},{"code_sha256_prefix":"5913de0c2ce8abf9","entry":"trans_gt_offset_format","repo":"xk-huang/yet-another-vectornet","repo_kind":"listed","path":"utils/feature_utils.py","file_url":"https://github.com/xk-huang/yet-another-vectornet/blob/HEAD/utils/feature_utils.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"Apache-2.0","inline_ok":true,"mcp_get_code":{"code_sha256":"5913de0c2ce8abf9"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}