{"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/exploiting-inter-image-similarity-and","title":"Exploiting inter-image similarity and ensemble of extreme learners for fixation prediction using deep features","arxiv_id":"1610.06449","date":"2016-10-20","proceeding":null,"authors":["Hamed R. -Tavakoli","Ali Borji","Jorma Laaksonen","Esa Rahtu"],"abstract":"This paper presents a novel fixation prediction and saliency modeling\nframework based on inter-image similarities and ensemble of Extreme Learning\nMachines (ELM). The proposed framework is inspired by two observations, 1) the\ncontextual information of a scene along with low-level visual cues modulates\nattention, 2) the influence of scene memorability on eye movement patterns\ncaused by the resemblance of a scene to a former visual experience. Motivated\nby such observations, we develop a framework that estimates the saliency of a\ngiven image using an ensemble of extreme learners, each trained on an image\nsimilar to the input image. That is, after retrieving a set of similar images\nfor a given image, a saliency predictor is learnt from each of the images in\nthe retrieved image set using an ELM, resulting in an ensemble. The saliency of\nthe given image is then measured in terms of the mean of predicted saliency\nvalue by the ensemble's members.","url_abs":"http://arxiv.org/abs/1610.06449v1","url_pdf":"http://arxiv.org/pdf/1610.06449v1.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":"exploiting-inter-image-similarity-and","repo_url":"https://github.com/hrtavakoli/iseel","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","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}