{"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/gomvs-geometrically-consistent-cost","title":"GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo","arxiv_id":"2404.07992","date":"2024-04-11","proceeding":"CVPR 2024 1","authors":["Jiang Wu","Rui Li","Haofei Xu","Wenxun Zhao","Yu Zhu","Jinqiu Sun","Yanning Zhang"],"abstract":"Matching cost aggregation plays a fundamental role in learning-based multi-view stereo networks. However, directly aggregating adjacent costs can lead to suboptimal results due to local geometric inconsistency. Related methods either seek selective aggregation or improve aggregated depth in the 2D space, both are unable to handle geometric inconsistency in the cost volume effectively. In this paper, we propose GoMVS to aggregate geometrically consistent costs, yielding better utilization of adjacent geometries. More specifically, we correspond and propagate adjacent costs to the reference pixel by leveraging the local geometric smoothness in conjunction with surface normals. We achieve this by the geometric consistent propagation (GCP) module. It computes the correspondence from the adjacent depth hypothesis space to the reference depth space using surface normals, then uses the correspondence to propagate adjacent costs to the reference geometry, followed by a convolution for aggregation. Our method achieves new state-of-the-art performance on DTU, Tanks & Temple, and ETH3D datasets. Notably, our method ranks 1st on the Tanks & Temple Advanced benchmark.","url_abs":"https://arxiv.org/abs/2404.07992v1","url_pdf":"https://arxiv.org/pdf/2404.07992v1.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":"gomvs-geometrically-consistent-cost","repo_url":"https://github.com/wuuu3511/gomvs","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/3d-reconstruction-on-dtu","task":"3D Reconstruction","dataset":"DTU","model":"GoMVS","rank_in_archive_order":2,"of":24,"metrics":{"Acc":"0.347","Comp":"0.227","Overall":"0.287"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2404.07992","atlas_url":"https://app.syntology.ai/?focus=2404.07992","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2404.07992"}},"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/wuuu3511/gomvs","reach":null}],"summary":{"unverified":6},"by_repo_kind":{"official":{"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":"15d90700a51b77a8","entry":"DepthNet","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"15d90700a51b77a8"}},{"code_sha256_prefix":"9a7fb145b19bcf61","entry":"GCACostRegNet","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"9a7fb145b19bcf61"}},{"code_sha256_prefix":"1d6afba428f5fcde","entry":"GoConv3D","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1d6afba428f5fcde"}},{"code_sha256_prefix":"45a830c85f426014","entry":"GoMVS","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"45a830c85f426014"}},{"code_sha256_prefix":"dc868b422dd3baef","entry":"GoUpConv3D","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"dc868b422dd3baef"}},{"code_sha256_prefix":"8a3a6c54a5a9b808","entry":"PixelwiseNet","repo":"wuuu3511/gomvs","repo_kind":"official","path":"models/GoMVSNet.py","file_url":"https://github.com/wuuu3511/gomvs/blob/HEAD/models/GoMVSNet.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"8a3a6c54a5a9b808"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}