CDER-SME provides 1,963 expert-annotated Event-RGB micro-expression samples from 92 subjects under multi-level stress, with a hardware-agnostic alignment pipeline and a multimodal baseline showing fusion gains.
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SAC²-Net uses semantic anchoring soft alignment and complementary-consensus fusion to report SOTA or competitive results on five MER benchmarks.
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CDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction
CDER-SME provides 1,963 expert-annotated Event-RGB micro-expression samples from 92 subjects under multi-level stress, with a hardware-agnostic alignment pipeline and a multimodal baseline showing fusion gains.
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SAC$^2$-Net: Semantic Anchoring and Complementary-Consensus Fusion for Multimodal Micro-Expression Recognition
SAC²-Net uses semantic anchoring soft alignment and complementary-consensus fusion to report SOTA or competitive results on five MER benchmarks.