{"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/voxel-field-fusion-for-3d-object-detection","title":"Voxel Field Fusion for 3D Object Detection","arxiv_id":"2205.15938","date":"2022-05-31","proceeding":"CVPR 2022 1","authors":["Yanwei Li","Xiaojuan Qi","Yukang Chen","LiWei Wang","Zeming Li","Jian Sun","Jiaya Jia"],"abstract":"In this work, we present a conceptually simple yet effective framework for cross-modality 3D object detection, named voxel field fusion. The proposed approach aims to maintain cross-modality consistency by representing and fusing augmented image features as a ray in the voxel field. To this end, the learnable sampler is first designed to sample vital features from the image plane that are projected to the voxel grid in a point-to-ray manner, which maintains the consistency in feature representation with spatial context. In addition, ray-wise fusion is conducted to fuse features with the supplemental context in the constructed voxel field. We further develop mixed augmentor to align feature-variant transformations, which bridges the modality gap in data augmentation. The proposed framework is demonstrated to achieve consistent gains in various benchmarks and outperforms previous fusion-based methods on KITTI and nuScenes datasets. Code is made available at https://github.com/dvlab-research/VFF.","url_abs":"https://arxiv.org/abs/2205.15938v1","url_pdf":"https://arxiv.org/pdf/2205.15938v1.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":"voxel-field-fusion-for-3d-object-detection","repo_url":"https://github.com/dvlab-research/vff","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"3d-object-detection","task_name":"3D Object Detection"},{"task_slug":"data-augmentation","task_name":"Data Augmentation"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[{"method_slug":"align","method_name":"ALIGN"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2205.15938","atlas_url":"https://app.syntology.ai/?focus=2205.15938","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2205.15938"}},"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/dvlab-research/vff","reach":{"status":"ok","spdx":"Apache-2.0"}},{"provenance":"deterministic:regex_extraction","url":"https://github.com/dvlab-research/VFF","reach":{"status":"ok","spdx":"Apache-2.0"}}],"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":0,"samples":[{"code_sha256_prefix":"476ca9d9bcfdb4d9","entry":"Point2ImageProjection","repo":"dvlab-research/VFF","repo_kind":"official","path":"pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","file_url":"https://github.com/dvlab-research/VFF/blob/HEAD/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","link_basis":"first_harvest_node","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":"476ca9d9bcfdb4d9"}},{"code_sha256_prefix":"26aabc41773af5e2","entry":"VoxelFieldFusion","repo":"dvlab-research/VFF","repo_kind":"official","path":"pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","file_url":"https://github.com/dvlab-research/VFF/blob/HEAD/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","link_basis":"first_harvest_node","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":"26aabc41773af5e2"}},{"code_sha256_prefix":"f997dee986da6db7","entry":"project_to_image","repo":"dvlab-research/VFF","repo_kind":"official","path":"pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","file_url":"https://github.com/dvlab-research/VFF/blob/HEAD/pcdet/models/backbones_3d/vfe/image_vfe_modules/f2v/voxel_field_fusion.py","link_basis":"first_harvest_node","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":"f997dee986da6db7"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}