6 papers
MAC 2026: Advancing Micro-Action Analysis Towards Fine-Grained Understanding
Kun Li, Dan Guo, Jihao Gu +6
Micro-Actions (MAs) are subtle and spontaneous human behaviors that provide important non-verbal cues in social interaction and affective communication. However, their short durati…
Concept-to-Pixel: Prompt-Free Universal Medical Image Segmentation
Haoyun Chen, Fenghe Tang, Wenxin Ma +1
Universal medical image segmentation seeks to use a single foundational model to handle diverse tasks across multiple imaging modalities. However, existing approaches often rely he…
Micro-AU CLIP: Fine-Grained Contrastive Learning from Local Independence to Global Dependency for Micro-Expression Action Unit Detection
Jinsheng Wei, Fengzhou Guo, Yante Li +3
Micro-expression (ME) action units (Micro-AUs) provide objective clues for fine-grained genuine emotion analysis. Most existing Micro-AU detection methods learn AU features from th…
FG-SGL: Fine-Grained Semantic Guidance Learning via Motion Process Decomposition for Micro-Gesture Recognition
Jinsheng Wei, Zhaodi Xu, Guanming Lu +2
Micro-gesture recognition (MGR) is challenging due to subtle inter-class variations. Existing methods rely on category-level supervision, which is insufficient for capturing subtle…
OmniFD: A Unified Model for Versatile Face Forgery Detection
Haotian Liu, Haoyu Chen, Chenhui Pan +3
Face forgery detection encompasses multiple critical tasks, including identifying forged images and videos and localizing manipulated regions and temporal segments. Current approac…
Vision Large Language Models Are Good Noise Handlers in Engagement Analysis
Alexander Vedernikov, Puneet Kumar, Haoyu Chen +2
Engagement recognition in video datasets, unlike traditional image classification tasks, is particularly challenged by subjective labels and noise limiting model performance. To ov…