{"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/color-constancy-using-cnns","title":"Color Constancy Using CNNs","arxiv_id":"1504.04548","date":"2015-04-17","proceeding":null,"authors":["Simone Bianco","Claudio Cusano","Raimondo Schettini"],"abstract":"In this work we describe a Convolutional Neural Network (CNN) to accurately\npredict the scene illumination. Taking image patches as input, the CNN works in\nthe spatial domain without using hand-crafted features that are employed by\nmost previous methods. The network consists of one convolutional layer with max\npooling, one fully connected layer and three output nodes. Within the network\nstructure, feature learning and regression are integrated into one optimization\nprocess, which leads to a more effective model for estimating scene\nillumination. This approach achieves state-of-the-art performance on a standard\ndataset of RAW images. Preliminary experiments on images with spatially varying\nillumination demonstrate the stability of the local illuminant estimation\nability of our CNN.","url_abs":"http://arxiv.org/abs/1504.04548v1","url_pdf":"http://arxiv.org/pdf/1504.04548v1.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":"color-constancy-using-cnns","repo_url":"https://github.com/rodroadl/CCCNN-pytorch","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"color-constancy","task_name":"Color Constancy"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1504.04548","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}