{"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/pathgan-visual-scanpath-prediction-with","title":"PathGAN: Visual Scanpath Prediction with Generative Adversarial Networks","arxiv_id":"1809.00567","date":"2018-09-03","proceeding":null,"authors":["Marc Assens","Xavier Giro-i-Nieto","Kevin McGuinness","Noel E. O'Connor"],"abstract":"We introduce PathGAN, a deep neural network for visual scanpath prediction\ntrained on adversarial examples. A visual scanpath is defined as the sequence\nof fixation points over an image defined by a human observer with its gaze.\nPathGAN is composed of two parts, the generator and the discriminator. Both\nparts extract features from images using off-the-shelf networks, and train\nrecurrent layers to generate or discriminate scanpaths accordingly. In scanpath\nprediction, the stochastic nature of the data makes it very difficult to\ngenerate realistic predictions using supervised learning strategies, but we\nadopt adversarial training as a suitable alternative. Our experiments prove how\nPathGAN improves the state of the art of visual scanpath prediction on the iSUN\nand Salient360! datasets. Source code and models are available at\nhttps://imatge-upc.github.io/pathgan/","url_abs":"http://arxiv.org/abs/1809.00567v1","url_pdf":"http://arxiv.org/pdf/1809.00567v1.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":"pathgan-visual-scanpath-prediction-with","repo_url":"https://github.com/imatge-upc/pathgan","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":{"status":"ok"}}],"tasks":[{"task_slug":"prediction","task_name":"Prediction"},{"task_slug":"scanpath-prediction","task_name":"Scanpath prediction"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1809.00567","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}