{"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/a-simple-baseline-for-audio-visual-scene","title":"A Simple Baseline for Audio-Visual Scene-Aware Dialog","arxiv_id":"1904.05876","date":"2019-04-11","proceeding":null,"authors":["Idan Schwartz Alexander Schwing","Tamir Hazan and"],"abstract":"The recently proposed audio-visual scene-aware dialog task paves the way to a\nmore data-driven way of learning virtual assistants, smart speakers and car\nnavigation systems. However, very little is known to date about how to\neffectively extract meaningful information from a plethora of sensors that\npound the computational engine of those devices. Therefore, in this paper, we\nprovide and carefully analyze a simple baseline for audio-visual scene-aware\ndialog which is trained end-to-end. Our method differentiates in a data-driven\nmanner useful signals from distracting ones using an attention mechanism. We\nevaluate the proposed approach on the recently introduced and challenging\naudio-visual scene-aware dataset, and demonstrate the key features that permit\nto outperform the current state-of-the-art by more than 20\\% on CIDEr.","url_abs":"http://arxiv.org/abs/1904.05876v1","url_pdf":"http://arxiv.org/pdf/1904.05876v1.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":"a-simple-baseline-for-audio-visual-scene","repo_url":"https://github.com/idansc/simple-avsd","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok"}}],"tasks":[],"methods":[{"method_slug":"fga","method_name":"FGA"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1904.05876","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}