8 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…
Rethinking the Role of Feature Engineering and Learning Strategies in Few-Shot Hidden Emotion Recognition
Xiaochuan Guo, Jihao Gu, Haixu Liu +6
In this paper, we present the solution developed by our team, XInsight Lab, which achieved first place in Track 3 of the 4th EI-MIGA-IJCAI Challenge with a test accuracy of 0.76923…
Self-supervised Learning Matters: A Simple Ensemble Solution for Micro-Gesture Recognition
Tingyi Liu, Kun Li, Fei Wang +5
In this paper, we present XInsight Lab's solution to the micro-gesture classification track of the 4th MiGA Challenge at IJCAI 2026, in which our solution ranked first and achieved…
Text-guided Fine-Grained Video Anomaly Understanding
Jihao Gu, Kun Li, He Wang +1
Subtle abnormal events in videos often manifest as weak spatio-temporal cues that are easily overlooked by conventional anomaly detection systems. Existing video anomaly detection…
MA-Bench: Towards Fine-grained Micro-Action Understanding
Kun Li, Jihao Gu, Fei Wang +3
With the rapid development of Multimodal Large Language Models (MLLMs), their potential in Micro-Action understanding, a vital role in human emotion analysis, remains unexplored du…
Motion Matters: Motion-guided Modulation Network for Skeleton-based Micro-Action Recognition
Jihao Gu, Kun Li, Fei Wang +4
Micro-Actions (MAs) are an important form of non-verbal communication in social interactions, with potential applications in human emotional analysis. However, existing methods in…