{"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/single-image-depth-estimation-by-dilated-deep","title":"Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference","arxiv_id":"1705.00534","date":"2017-04-27","proceeding":null,"authors":["Bo Li","Yuchao Dai","Huahui Chen","Mingyi He"],"abstract":"This paper proposes a new residual convolutional neural network (CNN)\narchitecture for single image depth estimation. Compared with existing deep CNN\nbased methods, our method achieves much better results with fewer training\nexamples and model parameters. The advantages of our method come from the usage\nof dilated convolution, skip connection architecture and soft-weight-sum\ninference. Experimental evaluation on the NYU Depth V2 dataset shows that our\nmethod outperforms other state-of-the-art methods by a margin.","url_abs":"http://arxiv.org/abs/1705.00534v1","url_pdf":"http://arxiv.org/pdf/1705.00534v1.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":"single-image-depth-estimation-by-dilated-deep","repo_url":"https://github.com/racinmat/depth-voxelmap-estimation","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"depth-estimation","task_name":"Depth Estimation"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}