{"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/an-attention-model-for-group-level-emotion","title":"An Attention Model for group-level emotion recognition","arxiv_id":"1807.03380","date":"2018-07-09","proceeding":null,"authors":["Aarush Gupta","Dakshit Agrawal","Hardik Chauhan","Jose Dolz","Marco Pedersoli"],"abstract":"In this paper we propose a new approach for classifying the global emotion of\nimages containing groups of people. To achieve this task, we consider two\ndifferent and complementary sources of information: i) a global representation\nof the entire image (ii) a local representation where only faces are\nconsidered. While the global representation of the image is learned with a\nconvolutional neural network (CNN), the local representation is obtained by\nmerging face features through an attention mechanism. The two representations\nare first learned independently with two separate CNN branches and then fused\nthrough concatenation in order to obtain the final group-emotion classifier.\nFor our submission to the EmotiW 2018 group-level emotion recognition\nchallenge, we combine several variations of the proposed model into an\nensemble, obtaining a final accuracy of 64.83% on the test set and ranking 4th\namong all challenge participants.","url_abs":"http://arxiv.org/abs/1807.03380v1","url_pdf":"http://arxiv.org/pdf/1807.03380v1.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":"an-attention-model-for-group-level-emotion","repo_url":"https://github.com/vlgiitr/Group-Level-Emotion-Recognition","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"},{"task_slug":"model","task_name":"model"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}