{"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/ultraman-single-image-3d-human-reconstruction","title":"Ultraman: Single Image 3D Human Reconstruction with Ultra Speed and Detail","arxiv_id":"2403.12028","date":"2024-03-18","proceeding":null,"authors":["Mingjin Chen","JunHao Chen","Xiaojun Ye","Huan-ang Gao","Xiaoxue Chen","Zhaoxin Fan","Hao Zhao"],"abstract":"3D human body reconstruction has been a challenge in the field of computer vision. Previous methods are often time-consuming and difficult to capture the detailed appearance of the human body. In this paper, we propose a new method called \\emph{Ultraman} for fast reconstruction of textured 3D human models from a single image. Compared to existing techniques, \\emph{Ultraman} greatly improves the reconstruction speed and accuracy while preserving high-quality texture details. We present a set of new frameworks for human reconstruction consisting of three parts, geometric reconstruction, texture generation and texture mapping. Firstly, a mesh reconstruction framework is used, which accurately extracts 3D human shapes from a single image. At the same time, we propose a method to generate a multi-view consistent image of the human body based on a single image. This is finally combined with a novel texture mapping method to optimize texture details and ensure color consistency during reconstruction. Through extensive experiments and evaluations, we demonstrate the superior performance of \\emph{Ultraman} on various standard datasets. In addition, \\emph{Ultraman} outperforms state-of-the-art methods in terms of human rendering quality and speed. Upon acceptance of the article, we will make the code and data publicly available.","url_abs":"https://arxiv.org/abs/2403.12028v1","url_pdf":"https://arxiv.org/pdf/2403.12028v1.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":"ultraman-single-image-3d-human-reconstruction","repo_url":"https://github.com/tomorrow1238/Ultraman","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"jax","reach":null}],"tasks":[{"task_slug":"lifelike-3d-human-generation","task_name":"Lifelike 3D Human Generation"}],"methods":[{"method_slug":"set","method_name":"SET"}],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/lifelike-3d-human-generation-on-thuman2-0","task":"Lifelike 3D Human Generation","dataset":"THuman2.0 Dataset","model":"Ultraman","rank_in_archive_order":2,"of":6,"metrics":{"CLIP Similarity":"0.9131","LPIPS":"0.1338","PSNR":"17.4877","SSIM":"0.8958"},"uses_additional_data":false}],"syntology":{"syntology_url":null,"atlas_url":"https://app.syntology.ai/?focus=2403.12028","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}