gewu-lab / awesome-audiovisual-learning Goto Github PK
View Code? Open in Web Editor NEWA curated list of audio-visual learning methods and datasets.
Home Page: https://gewu-lab.github.io/awesome-audiovisual-learning/
A curated list of audio-visual learning methods and datasets.
Home Page: https://gewu-lab.github.io/awesome-audiovisual-learning/
Hi,
Thanks for maintaining this list! I learned a lot from the listed papers ๐
I found this paper listed twice in the Audio-visual representation learning section:
[CVPR-2023] Vision Transformers are Parameter-Efficient Audio-Visual Learners
Authors: Yan-Bo Lin, Yi-Lin Sung, Jie Lei, Mohit Bansal, Gedas Bertasius
Institution: The University of North Carolina at Chapel Hill
Best,
Arthur
Hi,
Thanks for your efforts to build this great repo for audio-visual learning.
We recently have a study (HiCMAE) on self-supervised audio-visual emotion recognition and we hope it can be included in this awesome repo. Thanks very much!
Paper title: HiCMAE: Hierarchical Contrastive Masked Autoencoder for Self-Supervised Audio-Visual Emotion Recognition.
Codes and models: https://github.com/sunlicai/HiCMAE.
TL;DR: HiCMAE presents an early endeavor to leverage large-scale self-supervised pre-training to address the dilemma of current supervised methods and achieves great success on 9 audio-visual emotion recognition datasets.
Best,
Licai
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