{"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/large-scale-3d-shape-reconstruction-and","title":"Large-Scale 3D Shape Reconstruction and Segmentation from ShapeNet Core55","arxiv_id":"1710.06104","date":"2017-10-17","proceeding":null,"authors":["Li Yi","Lin Shao","Manolis Savva","Haibin Huang","Yang Zhou","Qirui Wang","Benjamin Graham","Martin Engelcke","Roman Klokov","Victor Lempitsky","Yuan Gan","Pengyu Wang","Kun Liu","Fenggen Yu","Panpan Shui","Bingyang Hu","Yan Zhang","Yangyan Li","Rui Bu","Mingchao Sun","Wei Wu","Minki Jeong","Jaehoon Choi","Changick Kim","Angom Geetchandra","Narasimha Murthy","Bhargava Ramu","Bharadwaj Manda","M. Ramanathan","Gautam Kumar","P Preetham","Siddharth Srivastava","Swati Bhugra","Brejesh lall","Christian Haene","Shubham Tulsiani","Jitendra Malik","Jared Lafer","Ramsey Jones","Siyuan Li","Jie Lu","Shi Jin","Jingyi Yu","Qi-Xing Huang","Evangelos Kalogerakis","Silvio Savarese","Pat Hanrahan","Thomas Funkhouser","Hao Su","Leonidas Guibas"],"abstract":"We introduce a large-scale 3D shape understanding benchmark using data and\nannotation from ShapeNet 3D object database. The benchmark consists of two\ntasks: part-level segmentation of 3D shapes and 3D reconstruction from single\nview images. Ten teams have participated in the challenge and the best\nperforming teams have outperformed state-of-the-art approaches on both tasks. A\nfew novel deep learning architectures have been proposed on various 3D\nrepresentations on both tasks. We report the techniques used by each team and\nthe corresponding performances. In addition, we summarize the major discoveries\nfrom the reported results and possible trends for the future work in the field.","url_abs":"http://arxiv.org/abs/1710.06104v2","url_pdf":"http://arxiv.org/pdf/1710.06104v2.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":"large-scale-3d-shape-reconstruction-and","repo_url":"https://github.com/facebookresearch/SparseConvNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"NOASSERTION"}}],"tasks":[{"task_slug":"3d-part-segmentation","task_name":"3D Part Segmentation"},{"task_slug":"3d-reconstruction","task_name":"3D Reconstruction"},{"task_slug":"3d-shape-reconstruction","task_name":"3D Shape Reconstruction"}],"methods":[{"method_slug":"sparse-convolutions","method_name":"Sparse Convolutions"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.06104","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}