CLAIP-Emo: Parameter-Efficient Adaptation of Language-supervised models for In-the-Wild Audiovisual Emotion Recognition
[2026.08.12] 🎉🎉Our new paper SSM has been accepted by IEEE Transactions on Affective Computing! A novel Structured Semantic Mapping framework for bidirectional learning between Facial Action Units and Facial Expressions under heterogeneous datasets.
[2026/07] CLAIP-Emo is accepted by IEEE Signal Processing Letters
[2026.7.18] 🎉🎉🚀🚀Our earlier work S2D was selected as the 2025 Best Paper Award (the only one!), for IEEE Transactions on Affective Computing by the IEEE Computer Society Publications Board.
If you find this work helpful, please consider citing:
@ARTICLE{11609236,
author={Chen, Yin and Li, Jia and Hu, Jinpeng and Hu, Zhenzhen and Hong, Richang},
journal={IEEE Signal Processing Letters},
title={CLAIP-Emo: Parameter-Efficient Adaptation of Language-Supervised Models for In-the-Wild Audiovisual Emotion Recognition},
year={2026},
volume={33},
number={},
pages={2989-2993},
@ARTICLE{11207542,
author={Chen, Yin and Li, Jia and Zhang, Yu and Hu, Zhenzhen and Shan, Shiguang and Wang, Meng and Hong, Richang},
journal={IEEE Transactions on Affective Computing},
title={Static for Dynamic: Towards a Deeper Understanding of Dynamic Facial Expressions Using Static Expression Data},
year={2026},
volume={17},
number={1},
pages={438-451},
}
@ARTICLE{10663980,
author={Chen, Yin and Li, Jia and Shan, Shiguang and Wang, Meng and Hong, Richang},
journal={IEEE Transactions on Affective Computing},
title={From Static to Dynamic: Adapting Landmark-Aware Image Models for Facial Expression Recognition in Videos},
year={2025},
volume={16},
number={2},
pages={624-638}}