{"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/hierarchical-prior-mining-for-non-local-multi","title":"Hierarchical Prior Mining for Non-local Multi-View Stereo","arxiv_id":"2303.09758","date":"2023-03-17","proceeding":"ICCV 2023 1","authors":["Chunlin Ren","Qingshan Xu","Shikun Zhang","Jiaqi Yang"],"abstract":"As a fundamental problem in computer vision, multi-view stereo (MVS) aims at recovering the 3D geometry of a target from a set of 2D images. Recent advances in MVS have shown that it is important to perceive non-local structured information for recovering geometry in low-textured areas. In this work, we propose a Hierarchical Prior Mining for Non-local Multi-View Stereo (HPM-MVS). The key characteristics are the following techniques that exploit non-local information to assist MVS: 1) A Non-local Extensible Sampling Pattern (NESP), which is able to adaptively change the size of sampled areas without becoming snared in locally optimal solutions. 2) A new approach to leverage non-local reliable points and construct a planar prior model based on K-Nearest Neighbor (KNN), to obtain potential hypotheses for the regions where prior construction is challenging. 3) A Hierarchical Prior Mining (HPM) framework, which is used to mine extensive non-local prior information at different scales to assist 3D model recovery, this strategy can achieve a considerable balance between the reconstruction of details and low-textured areas. Experimental results on the ETH3D and Tanks \\& Temples have verified the superior performance and strong generalization capability of our method. Our code will be released.","url_abs":"https://arxiv.org/abs/2303.09758v1","url_pdf":"https://arxiv.org/pdf/2303.09758v1.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":"hierarchical-prior-mining-for-non-local-multi","repo_url":"https://github.com/CLinvx/HPM-MVS","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"3d-geometry","task_name":"3D geometry"},{"task_slug":"multi-view-3d-reconstruction","task_name":"Multi-View 3D Reconstruction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/multi-view-3d-reconstruction-on-eth3d","task":"Multi-View 3D Reconstruction","dataset":"ETH3D","model":"HPM-MVS","rank_in_archive_order":3,"of":5,"metrics":{"F1 score":"87.11"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/2303.09758","atlas_url":"https://app.syntology.ai/?focus=2303.09758","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}