{"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/computing-the-stereo-matching-cost-with-a","title":"Computing the Stereo Matching Cost with a Convolutional Neural Network","arxiv_id":"1409.4326","date":"2014-09-15","proceeding":"CVPR 2015 6","authors":["Jure Žbontar","Yann Lecun"],"abstract":"We present a method for extracting depth information from a rectified image\npair. We train a convolutional neural network to predict how well two image\npatches match and use it to compute the stereo matching cost. The cost is\nrefined by cross-based cost aggregation and semiglobal matching, followed by a\nleft-right consistency check to eliminate errors in the occluded regions. Our\nstereo method achieves an error rate of 2.61 % on the KITTI stereo dataset and\nis currently (August 2014) the top performing method on this dataset.","url_abs":"http://arxiv.org/abs/1409.4326v2","url_pdf":"http://arxiv.org/pdf/1409.4326v2.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":"computing-the-stereo-matching-cost-with-a","repo_url":"https://github.com/leduoyang/depth_estimation_MCCNN","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok"}}],"tasks":[{"task_slug":"stereo-matching-1","task_name":"Stereo Matching"},{"task_slug":"stereo-matching","task_name":"Stereo Matching Hand"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1409.4326","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}