{"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/how-deep-neural-networks-can-improve-emotion","title":"How Deep Neural Networks Can Improve Emotion Recognition on Video Data","arxiv_id":"1602.07377","date":"2016-02-24","proceeding":null,"authors":["Pooya Khorrami","Tom Le Paine","Kevin Brady","Charlie Dagli","Thomas S. Huang"],"abstract":"We consider the task of dimensional emotion recognition on video data using\ndeep learning. While several previous methods have shown the benefits of\ntraining temporal neural network models such as recurrent neural networks\n(RNNs) on hand-crafted features, few works have considered combining\nconvolutional neural networks (CNNs) with RNNs. In this work, we present a\nsystem that performs emotion recognition on video data using both CNNs and\nRNNs, and we also analyze how much each neural network component contributes to\nthe system's overall performance. We present our findings on videos from the\nAudio/Visual+Emotion Challenge (AV+EC2015). In our experiments, we analyze the\neffects of several hyperparameters on overall performance while also achieving\nsuperior performance to the baseline and other competing methods.","url_abs":"http://arxiv.org/abs/1602.07377v5","url_pdf":"http://arxiv.org/pdf/1602.07377v5.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":"how-deep-neural-networks-can-improve-emotion","repo_url":"https://github.com/DenisRang/Combined-CNN-RNN-for-emotion-recognition","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}