A decoupled adapter with independent spatial-temporal branches via depthwise convolutions and a dynamic augmentation strategy for long-tail data achieves first place with F1 0.43808 in a micro-gesture recognition challenge.
arXiv preprint arXiv:2503.15978 (2025)
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FPED is a functional-network prior-guided MoE framework for fMRI visual reconstruction that claims competitive performance at 0.68B parameters and biologically meaningful routing interpretability.
A multi-modal system combining skeleton/heatmap/RGB features with cross-modal pseudo-labeling and semantic losses achieves 68.13% F1-score and 4th place on the MiGA-IJCAI micro-gesture challenge.
DyFADet+ extends a prior detector with gated RGB-skeleton fusion and reports 40.88 F1 on the SMG dataset for micro-gesture online recognition.
citing papers explorer
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Spatial-Temporal Decoupled Adapter for Micro-gesture Online Recognition
A decoupled adapter with independent spatial-temporal branches via depthwise convolutions and a dynamic augmentation strategy for long-tail data achieves first place with F1 0.43808 in a micro-gesture recognition challenge.
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FPED: A Functional-Network Prior-Guided Mixture-of-Experts Framework for Interpretable Brain Decoding
FPED is a functional-network prior-guided MoE framework for fMRI visual reconstruction that claims competitive performance at 0.68B parameters and biologically meaningful routing interpretability.
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A Multi-Modal Framework with Cross-Subject Pseudo-Labeling and Semantic Alignment for Micro-Gesture Recognition
A multi-modal system combining skeleton/heatmap/RGB features with cross-modal pseudo-labeling and semantic losses achieves 68.13% F1-score and 4th place on the MiGA-IJCAI micro-gesture challenge.
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Motion Reinforces Appearance: RGB-Skeleton Gated Residual Fusion for Micro-Gesture Online Recognition
DyFADet+ extends a prior detector with gated RGB-skeleton fusion and reports 40.88 F1 on the SMG dataset for micro-gesture online recognition.