{"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/saliency-map-estimation-for-omni-directional","title":"Saliency Map Estimation for Omni-Directional Image Considering Prior Distributions","arxiv_id":"1807.06329","date":"2018-07-17","proceeding":null,"authors":["Tatsuya Suzuki","Takao Yamanaka"],"abstract":"In recent years, the deep learning techniques have been applied to the\nestimation of saliency maps, which represent probability density functions of\nfixations when people look at the images. Although the methods of saliency-map\nestimation have been actively studied for 2-dimensional planer images, the\nmethods for omni-directional images to be utilized in virtual environments had\nnot been studied, until a competition of saliency-map estimation for the\nomni-directional images was held in ICME2017. In this paper, novel methods for\nestimating saliency maps for the omni-directional images are proposed\nconsidering the properties of prior distributions for fixations in the planar\nimages and the omni-directional images.","url_abs":"http://arxiv.org/abs/1807.06329v1","url_pdf":"http://arxiv.org/pdf/1807.06329v1.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":"saliency-map-estimation-for-omni-directional","repo_url":"https://github.com/islab-sophia/odisal","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}