{"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/end-to-end-convolutional-network-for-saliency","title":"End-to-end Convolutional Network for Saliency Prediction","arxiv_id":"1507.01422","date":"2015-07-06","proceeding":null,"authors":["Junting Pan","Xavier Giró-i-Nieto"],"abstract":"The prediction of saliency areas in images has been traditionally addressed\nwith hand crafted features based on neuroscience principles. This paper however\naddresses the problem with a completely data-driven approach by training a\nconvolutional network. The learning process is formulated as a minimization of\na loss function that measures the Euclidean distance of the predicted saliency\nmap with the provided ground truth. The recent publication of large datasets of\nsaliency prediction has provided enough data to train a not very deep\narchitecture which is both fast and accurate. The convolutional network in this\npaper, named JuntingNet, won the LSUN 2015 challenge on saliency prediction\nwith a superior performance in all considered metrics.","url_abs":"http://arxiv.org/abs/1507.01422v1","url_pdf":"http://arxiv.org/pdf/1507.01422v1.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":"end-to-end-convolutional-network-for-saliency","repo_url":"https://github.com/imatge-upc/saliency-2016-lsun","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"saliency-prediction","task_name":"Saliency Prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}