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20242026
most citedEnhancing Micro Gesture Recognition for Emotion Understanding via Context-aware Visual-Text Contrastive Learning

23 citations · 31 across the 10 of their papers we have counts for

collaborators

12 papers

cs.CV2026

Do Emotion Concepts Generalize Across Sources, Modalities, and Architectures in Vision-Language Models?

Bohao Xing, Xin Liu, Kaishen Yuan +5

Recent studies suggest that large language models encode emotion concepts as structured internal representations, but most existing work focuses on text and a single architecture.…

cs.CV2026

Insights from Visual Cognition: Understanding Human Action Dynamics with Overall Glance and Refined Gaze Transformer

Bohao Xing, Deng Li, Rong Gao +2

Recently, Transformer has made significant progress in various vision tasks. To balance computation and efficiency in video tasks, recent works heavily rely on factorized or window…

cs.CV2025

MSF-Mamba: Motion-aware State Fusion Mamba for Efficient Micro-Gesture Recognition

Deng Li, Jun Shao, Bohao Xing +4

Micro-gesture recognition (MGR) targets the identification of subtle and fine-grained human motions and requires accurate modeling of both long-range and local spatiotemporal depen…

cs.CV2025

EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models

Bohao Xing, Xin Liu, Guoying Zhao +3

Emotion understanding is a critical yet challenging task. Recent advances in Multimodal Large Language Models (MLLMs) have significantly enhanced their capabilities in this area. H…

cs.CV2025

FSBench: A Figure Skating Benchmark for Advancing Artistic Sports Understanding

Rong Gao, Xin Liu, Zhuozhao Hu +4

Figure skating, known as the "Art on Ice," is among the most artistic sports, challenging to understand due to its blend of technical elements (like jumps and spins) and overall ar…

cs.CV2025★ 6 cited

DEEMO: De-identity Multimodal Emotion Recognition and Reasoning

Deng Li, Bohao Xing, Xin Liu +3

Emotion understanding is a critical yet challenging task. Most existing approaches rely heavily on identity-sensitive information, such as facial expressions and speech, which rais…

cs.CV2025

AU-TTT: Vision Test-Time Training model for Facial Action Unit Detection

Bohao Xing, Kaishen Yuan, Zitong Yu +2

Facial Action Units (AUs) detection is a cornerstone of objective facial expression analysis and a critical focus in affective computing. Despite its importance, AU detection faces…

cs.LG2024

scFusionTTT: Single-cell transcriptomics and proteomics fusion with Test-Time Training layers

Dian Meng, Bohao Xing, Xinlei Huang +5

Single-cell multi-omics (scMulti-omics) refers to the paired multimodal data, such as Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq), where the regulatio…

cs.CV2024

EMO-LLaMA: Enhancing Facial Emotion Understanding with Instruction Tuning

Bohao Xing, Zitong Yu, Xin Liu +6

Facial expression recognition (FER) is an important research topic in emotional artificial intelligence. In recent decades, researchers have made remarkable progress. However, curr…

cs.CV2024★ 23 cited

Enhancing Micro Gesture Recognition for Emotion Understanding via Context-aware Visual-Text Contrastive Learning

Deng Li, Bohao Xing, Xin Liu

Psychological studies have shown that Micro Gestures (MG) are closely linked to human emotions. MG-based emotion understanding has attracted much attention because it allows for em…

cs.CV2024★ 2 cited

Identity-free Artificial Emotional Intelligence via Micro-Gesture Understanding

Rong Gao, Xin Liu, Bohao Xing +3

In this work, we focus on a special group of human body language -- the micro-gesture (MG), which differs from the range of ordinary illustrative gestures in that they are not inte…

cs.CV2024

EALD-MLLM: Emotion Analysis in Long-sequential and De-identity videos with Multi-modal Large Language Model

Deng Li, Xin Liu, Bohao Xing +4

Emotion AI is the ability of computers to understand human emotional states. Existing works have achieved promising progress, but two limitations remain to be solved: 1) Previous s…