7 papers · 1 filter
DeceptionX: From Multimodal Evidence to Explainable Deception Detection
Jiayu Zhang, Shuo Ye, Jiajian Huang +8
Deception detection is a critical and highly challenging task within affective computing and behavioral analysis. Existing deep learning methods typically treat this task as a stra…
GMoT: Gated Motion-Aware Tokenization for Fine-Grained Micro-Gesture Video Reasoning with Multimodal LLMs
Taorui Wang, Wei Xia, Hui Ma +5
Micro-gesture recognition demands the detection of fleeting, spatially localized movements that are frequently overwhelmed by dominant static appearances and background noise. Whil…
OracleAnalyser: Analysing Implicit Semantics of Oracle Bone Scripts through MLLMs with Post-training
Zijia Song, Yelin Wang, Zhengyi Ma +5
With the advancement of artificial intelligence, research on oracle bone scripts has entered a new era. However, existing methods and benchmarks remain largely confined to recognit…
SVC 2026: the Second Multimodal Deception Detection Challenge and the First Domain Generalized Remote Physiological Measurement Challenge
Dongliang Zhu, Zhiyi Niu, Bo Zhao +14
Subtle visual signals, although difficult to perceive with the naked eye, contain important information that can reveal hidden patterns in visual data. These signals play a key rol…
AffectAgent: Collaborative Multi-Agent Reasoning for Retrieval-Augmented Multimodal Emotion Recognition
Zeheng Wang, Zitong Yu, Yijie Zhu +9
LLM-based multimodal emotion recognition relies on static parametric memory and often hallucinates when interpreting nuanced affective states. In this paper, given that single-roun…
SVC 2025: the First Multimodal Deception Detection Challenge
Xun Lin, Xiaobao Guo, Taorui Wang +5
Deception detection is a critical task in real-world applications such as security screening, fraud prevention, and credibility assessment. While deep learning methods have shown p…