Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition

Cosmo can effectively extract both consistent and complementary information across different modalities for efficient fusion by integrating novel fusion-based contrastive learning and quality-guided attention mechanisms.
Reference
Xiaomin Ouyang , Xian ShuaiJiayu Zhou, Ivy Wang Shi, Zhiyuan XieGuoliang Xing , and Jianwei Huang. Cosmo: Contrastive Fusion Learning with Small Data for Multimodal Human Activity Recognition In The 28th Annual International Conference on Mobile Computing and Networking (Acceptance rate: 56/317=17.7%), 2022