{"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/deep-cuboid-detection-beyond-2d-bounding","title":"Deep Cuboid Detection: Beyond 2D Bounding Boxes","arxiv_id":"1611.10010","date":"2016-11-30","proceeding":null,"authors":["Debidatta Dwibedi","Tomasz Malisiewicz","Vijay Badrinarayanan","Andrew Rabinovich"],"abstract":"We present a Deep Cuboid Detector which takes a consumer-quality RGB image of\na cluttered scene and localizes all 3D cuboids (box-like objects). Contrary to\nclassical approaches which fit a 3D model from low-level cues like corners,\nedges, and vanishing points, we propose an end-to-end deep learning system to\ndetect cuboids across many semantic categories (e.g., ovens, shipping boxes,\nand furniture). We localize cuboids with a 2D bounding box, and simultaneously\nlocalize the cuboid's corners, effectively producing a 3D interpretation of\nbox-like objects. We refine keypoints by pooling convolutional features\niteratively, improving the baseline method significantly. Our deep learning\ncuboid detector is trained in an end-to-end fashion and is suitable for\nreal-time applications in augmented reality (AR) and robotics.","url_abs":"http://arxiv.org/abs/1611.10010v1","url_pdf":"http://arxiv.org/pdf/1611.10010v1.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":"deep-cuboid-detection-beyond-2d-bounding","repo_url":"https://github.com/rubenve95/Deep-Cuboid-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1611.10010","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}