COMODO is a cross-modal self-supervised distillation framework that uses a frozen video encoder and dynamic instance queue to align video and IMU embeddings, improving IMU-based egocentric HAR to match supervised performance.
Towards continual egocentric activity recognition: A multi-modal egocentric activity dataset for continual learn- ing
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COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity Recognition
COMODO is a cross-modal self-supervised distillation framework that uses a frozen video encoder and dynamic instance queue to align video and IMU embeddings, improving IMU-based egocentric HAR to match supervised performance.