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Understanding emotions accurately is essential for fields like human-computer interaction.
Afew-va database for valence and arousal estimation in-the-wild
Jean Kossaifi, Georgios Tzimiropoulos, Sinisa Todorovic, and Maja Pantic · 2017
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Simple online and realtime tracking with a deep association metric
Nicolai Wojke, Alex Bewley, and Dietrich Paulus · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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The ryerson audio-visual database of emotional speech and song (ravdess): A dynamic, multimodal set of facial and vocal expressions in north american english
Steven R Livingstone and Frank A Russo · 2018
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Multimodal language analysis in the wild: Cmu-mosei dataset and interpretable dynamic fusion graph
AmirAli Bagher Zadeh, Paul Pu Liang, Soujanya Poria, Erik Cambria, and Louis-Philippe Morency · 2018
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Common voice: A massively-multilingual speech corpus
Rosana Ardila, Megan Branson, Kelly Davis, Michael Henretty, Michael Kohler, Josh Meyer, Reuben Morais, Lindsay Saunders, Francis M Tyers, and Gregor Weber · 2019
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Retinaface: Single-stage dense face localisation in the wild
Jiankang Deng, Jia Guo, Yuxiang Zhou, Jinke Yu, Irene Kotsia, and Stefanos Zafeiriou · 2019
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Context-aware emotion recognition networks
Jiyoung Lee, Seungryong Kim, Sunok Kim, Jungin Park, and Kwanghoon Sohn · 2019
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Exploring emotion features and fusion strategies for audio-video emotion recognition
Hengshun Zhou, Debin Meng, Yuanyuan Zhang, Xiaojiang Peng, Jun Du, Kai Wang, and Yu Qiao · 2019
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wav2vec 2.0: A framework for self-supervised learning of speech representations
Alexei Baevski, Yuhao Zhou, Abdelrahman Mohamed, and Michael Auli · 2020
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Vggsound: A large-scale audio-visual dataset
Honglie Chen, Weidi Xie, Andrea Vedaldi, and Andrew Zisserman · 2020
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Dfew: A large-scale database for recognizing dynamic facial expressions in the wild
Xingxun Jiang, Yuan Zong, Wenming Zheng, Chuangao Tang, Wanchuang Xia, Cheng Lu, and Jiateng Liu · 2020
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Suppressing uncertainties for large-scale facial expression recognition
Kai Wang, Xiaojiang Peng, Jianfei Yang, Shijian Lu, and Yu Qiao · 2020
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Lssed: a large-scale dataset and benchmark for speech emotion recognition
Weiquan Fan, Xiangmin Xu, Xiaofen Xing, Weidong Chen, and Dongyan Huang · 2021
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Hubert: Self-supervised speech representation learning by masked prediction of hidden units
Wei-Ning Hsu, Benjamin Bolte, Yao-Hung Hubert Tsai, Kushal Lakhotia, Ruslan Salakhutdinov, and Abdelrahman Mohamed · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
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Flamingo: a visual language model for few-shot learning
Jean-Baptiste Alayrac, Jeff Donahue, Pauline Luc, Antoine Miech, Iain Barr, Yana Hasson, Karel Lenc, Arthur Mensch, Katherine Millican, Malcolm Reynolds, et al · 2022
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Large raw emotional dataset with aggregation mechanism
Vladimir Kondratenko, Artem Sokolov, Nikolay Karpov, Oleg Kutuzov, Nikita Savushkin, and Fyodor Minkin · 2022
Cited alongside, same era.
Mafw: A large-scale, multi-modal, compound affective database for dynamic facial expression recognition in the wild
Yuanyuan Liu, Wei Dai, Chuanxu Feng, Wenbin Wang, Guanghao Yin, Jiabei Zeng, and Shiguang Shan · 2022
Cited alongside, same era.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
Cited alongside, same era.
Ferv39k: A large-scale multi-scene dataset for facial expression recognition in videos
Yan Wang, Yixuan Sun, Yiwen Huang, Zhongying Liu, Shuyong Gao, Wei Zhang, Weifeng Ge, and Wenqiang Zhang · 2022
Pandagpt: One model to instruction-follow them all
Yixuan Su, Tian Lan, Huayang Li, Jialu Xu, Yan Wang, and Deng Cai · 2023
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Mae-dfer: Efficient masked autoencoder for self-supervised dynamic facial expression recognition
Licai Sun, Zheng Lian, Bin Liu, and Jianhua Tao · 2023
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Visionllm: Large language model is also an open-ended decoder for vision-centric tasks
Wenhai Wang, Zhe Chen, Xiaokang Chen, Jiannan Wu, Xizhou Zhu, Gang Zeng, Ping Luo, Tong Lu, Jie Zhou, Yu Qiao, et al · 2023
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Sigmoid loss for language image pre-training
Xiaohua Zhai, Basil Mustafa, Alexander Kolesnikov, and Lucas Beyer · 2023
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Prompting visual-language models for dynamic facial expression recognition
Zengqun Zhao and Ioannis Patras · 2023
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Cited alongside, same era.
Qwen-vl: A frontier large vision-language model with versatile abilities
Jinze Bai, Shuai Bai, Shusheng Yang, Shijie Wang, Sinan Tan, Peng Wang, Junyang Lin, Chang Zhou, and Jingren Zhou · 2023
Cited alongside, same era.
Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
Cited alongside, same era.
Beyond sentiment analysis: A review of recent trends in text based sentiment analysis and emotion detection
Lai Po Hung and Suraya Alias · 2023
Cited alongside, same era.
Mivolo: Multi-input transformer for age and gender estimation
Maksim Kuprashevich and Irina Tolstykh · 2023
Cited alongside, same era.
Shanglin Lei, Guanting Dong, Xiaoping Wang, Keheng Wang, and Sirui Wang · 2023
Cited alongside, same era.
Explainable multimodal emotion reasoning
Zheng Lian, Licai Sun, Mingyu Xu, Haiyang Sun, Ke Xu, Zhuofan Wen, Shun Chen, Bin Liu, and Jianhua Tao · 2023
Cited alongside, same era.
Valley: Video assistant with large language model enhanced ability
Ruipu Luo, Ziwang Zhao, Min Yang, Junwei Dong, Minghui Qiu, Pengcheng Lu, Tao Wang, and Zhongyu Wei · 2023
Cited alongside, same era.
Minigpt-4: Enhancing vision-language understanding with advanced large language models
Deyao Zhu, Jun Chen, Xiaoqian Shen, Xiang Li, and Mohamed Elhoseiny · 2023
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Emotion-llama: Multimodal emotion recognition and reasoning with instruction tuning
Zebang Cheng, Zhi-Qi Cheng, Jun-Yan He, Jingdong Sun, Kai Wang, Yuxiang Lin, Zheng Lian, Xiaojiang Peng, and Alexander Hauptmann · 2024
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Yunfei Chu, Jin Xu, Qian Yang, Haojie Wei, Xipin Wei, Zhifang Guo, Yichong Leng, Yuanjun Lv, Jinzheng He, Junyang Lin, Chang Zhou, and Jingren Zhou · 2024
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Mma-dfer: Multimodal adaptation of unimodal models for dynamic facial expression recognition in-the-wild
Kateryna Chumachenko, Alexandros Iosifidis, and Moncef Gabbouj · 2024
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Zheng Lian, Haiyang Sun, Licai Sun, Zhuofan Wen, Siyuan Zhang, Shun Chen, Hao Gu, Jinming Zhao, Ziyang Ma, Xie Chen, et al · 2024
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Visual instruction tuning
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2024
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Wavcaps: A chatgpt-assisted weakly-labelled audio captioning dataset for audio-language multimodal research
Xinhao Mei, Chutong Meng, Haohe Liu, Qiuqiang Kong, Tom Ko, Chengqi Zhao, Mark D Plumbley, Yuexian Zou, and Wenwu Wang · 2024
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Facexformer: A unified transformer for facial analysis
Kartik Narayan, Vibashan VS, Rama Chellappa, and Vishal M Patel · 2024
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Cambrian-1: A fully open, vision-centric exploration of multimodal llms
Shengbang Tong, Ellis Brown, Penghao Wu, Sanghyun Woo, Manoj Middepogu, Sai Charitha Akula, Jihan Yang, Shusheng Yang, Adithya Iyer, Xichen Pan, et al · 2024
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Emovit: Revolutionizing emotion insights with visual instruction tuning
Hongxia Xie, Chu-Jun Peng, Yu-Wen Tseng, Hung-Jen Chen, Chan-Feng Hsu, Hong-Han Shuai, and Wen-Huang Cheng · 2024
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