CDER-SME:跨设备事件-RGB微表情数据集及多级别压力诱导研究
Computer Science > Computer Vision and Pattern Recognition
• *arXiv:2606.20715** (cs)
[Submitted on 16 Jun 2026]
Title:CDER-SME: A Cross-Device Event-RGB Micro-Expression Dataset under Multi-Level Stress Induction
Authors: Jingting Li (https://arxiv.org/search/cs?searchtype=author&query=Li,+J), Hui Sha (https://arxiv.org/search/cs?searchtype=author&query=Sha,+H), Su-Jing Wang (https://arxiv.org/search/cs?searchtype=author&query=Wang,+S)
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Abstract:Micro-expression recognition (MER) in realistic scenarios demands high temporal sensitivity and ecological validity, yet existing benchmarks are largely constrained to laboratory-controlled settings and rigid hardware-coupled sensing. We introduce CDER-SME, a cross-device Event-RGB dataset collected under a multi-level stress induction framework (cognitive and social) to elicit spontaneous emotional leakage. To enable reproducible acquisition with independent, decoupled sensors, we provide a hardware-agnostic alignment pipeline for temporal synchronization and landmark-guided spatial registration. CDER-SME adopts a three-tier structure with 92 subjects and 1,963 expert-annotated samples (Action Units and emotions), including 790 Event-RGB pairs and 210 high-fidelity aligned pairs. We further report a reproducible multimodal baseline, where cross-modal fusion improves performance over single-modality counterparts, supporting the complementarity of event dynamics and RGB cues. By removing the need for coaxial calibration, CDER-SME offers a practical benchmark for cross-device alignment and deployable Event-RGB MER in real-world affective intelligence.
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From: Su-Jing Wang [view email (https://arxiv.org/show-email/a12702ca/2606.20715)]
• *[v1]**
Tue, 16 Jun 2026 14:07:27 UTC (6,460 KB)
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