{"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/oasis-a-large-scale-dataset-for-single-image-1","title":"OASIS: A Large-Scale Dataset for Single Image 3D in the Wild","arxiv_id":"2007.13215","date":"2020-07-26","proceeding":"CVPR 2020 6","authors":["Weifeng Chen","Shengyi Qian","David Fan","Noriyuki Kojima","Max Hamilton","Jia Deng"],"abstract":"Single-view 3D is the task of recovering 3D properties such as depth and surface normals from a single image. We hypothesize that a major obstacle to single-image 3D is data. We address this issue by presenting Open Annotations of Single Image Surfaces (OASIS), a dataset for single-image 3D in the wild consisting of annotations of detailed 3D geometry for 140,000 images. We train and evaluate leading models on a variety of single-image 3D tasks. We expect OASIS to be a useful resource for 3D vision research. Project site: https://pvl.cs.princeton.edu/OASIS.","url_abs":"https://arxiv.org/abs/2007.13215v1","url_pdf":"https://arxiv.org/pdf/2007.13215v1.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":[],"tasks":[{"task_slug":"3d-geometry","task_name":"3D geometry"}],"methods":[],"datasets_introduced":[{"slug":"oasis","name":"OASIS","full_name":"Open Annotations of Single Image Surfaces"}],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2007.13215","atlas_url":"https://app.syntology.ai/?focus=2007.13215","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}