
Utilizing temporal convolution and GPT-2 enhances AU detection accuracy by integrating audio-visual data for nuanced emotional expression understanding.


coremsg

advancing-action-unit-detection-with-temporal-convolution-and-gpt-2-in-wild-audiovisual-contexts


Advancing Action Unit Detection with Temporal Convolution and GPT-2 in Wild Audiovisual Contexts


title_rewrite


The author presents the first publicly available multimodal dataset, REWIND, for speaking status segmentation from body movement in real-life mingling scenarios with high-quality audio recordings.


REWIND-Dataset-Privacy-preserving-Speaking-Status-Segmentation-from-Multimodal-Body-Movement-Signals-in-the-Wild


REWIND Dataset: Privacy-preserving Speaking Status Segmentation from Multimodal Body Movement Signals in the Wild
