{"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/surface-from-gradients-an-approach-based-on","title":"Surface-from-Gradients: An Approach Based on Discrete Geometry Processing","arxiv_id":null,"date":"2014-06-01","proceeding":"CVPR 2014 6","authors":["Wuyuan Xie","Yunbo Zhang","Charlie C. L. Wang","Ronald C.-K. Chung"],"abstract":"In this paper, we propose an efficient method to reconstruct surface-from-gradients (SfG). Our method is formulated under the framework of discrete geometry processing. Unlike the existing SfG approaches, we transfer the continuous reconstruction problem into a discrete space and efficiently solve the problem via a sequence of least-square optimization steps. Our discrete formulation brings three advantages: 1) the reconstruction preserves sharp-features, 2) sparse/incomplete set of gradients can be well handled, and 3) domains of computation can have irregular boundaries. Our formulation is direct and easy to implement, and the comparisons with state-of-the-arts show the effectiveness of our method.","url_abs":"http://openaccess.thecvf.com/content_cvpr_2014/html/Xie_Surface-from-Gradients_An_Approach_2014_CVPR_paper.html","url_pdf":"http://openaccess.thecvf.com/content_cvpr_2014/papers/Xie_Surface-from-Gradients_An_Approach_2014_CVPR_paper.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":"surface-from-gradients-an-approach-based-on","repo_url":"https://github.com/kwong292521/DGP","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}