{"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/unstructured-multi-view-depth-estimation","title":"Unstructured Multi-View Depth Estimation Using Mask-Based Multiplane Representation","arxiv_id":"1902.02166","date":"2019-02-06","proceeding":null,"authors":["Yuxin Hou","Arno Solin","Juho Kannala"],"abstract":"This paper presents a novel method, MaskMVS, to solve depth estimation for\nunstructured multi-view image-pose pairs. In the plane-sweep procedure, the\ndepth planes are sampled by histogram matching that ensures covering the depth\nrange of interest. Unlike other plane-sweep methods, we do not rely on a cost\nmetric to explicitly build the cost volume, but instead infer a multiplane mask\nrepresentation which regularizes the learning. Compared to many previous\napproaches, we show that our method is lightweight and generalizes well without\nrequiring excessive training. We outperform the current state-of-the-art and\nshow results on the sun3d, scenes11, MVS, and RGBD test data sets.","url_abs":"http://arxiv.org/abs/1902.02166v2","url_pdf":"http://arxiv.org/pdf/1902.02166v2.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":"unstructured-multi-view-depth-estimation","repo_url":"https://github.com/AaltoVision/MaskMVS","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"depth-estimation","task_name":"Depth Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}