CM3T shows that multi-head vision adapters plus cross-attention adapters can adapt frozen supervised-pretrained video transformers with a fraction of the trainable parameters of full fine-tuning.
Bodily be- haviors in social interaction: Novel annotations and state-of- the-art evaluation
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CM3T: Framework for Efficient Multimodal Learning for Inhomogeneous Interaction Datasets
CM3T shows that multi-head vision adapters plus cross-attention adapters can adapt frozen supervised-pretrained video transformers with a fraction of the trainable parameters of full fine-tuning.