Motion Reinforces Appearance: RGB-Skeleton Gated Residual Fusion for Micro-Gesture Online Recognition
Researchers have developed a new dual-stream framework called DyFADet+ for recognizing micro-gestures in untrimmed videos. This method fuses RGB and skeleton data through a gated residual module, allowing skeleton motion to enhance the RGB representation. The system achieved an F1 score of 40.88 on the SMG dataset, securing second place in the Micro-gesture Online Recognition track of the 4th EI-MiGA-IJCAI Challenge. AI
IMPACT Introduces a novel fusion technique for multimodal gesture recognition, potentially improving human-computer interaction systems.