3 citations · 6 across the 12 of their papers we have counts for
13 papers
Dynamic Collaboration of Multi-Language Models based on Minimal Complete Semantic Units
Chao Hao, Zezheng Wang, Yanhua Huang +4
This paper investigates the enhancement of reasoning capabilities in language models through token-level multi-model collaboration. Our approach selects the optimal tokens from the…
Distribution-Specific Learning for Joint Salient and Camouflaged Object Detection
Chao Hao, Zitong Yu, Xin Liu +5
Salient object detection (SOD) and camouflaged object detection (COD) are two closely related but distinct computer vision tasks. Although both are class-agnostic segmentation task…
AU-LLM: Micro-Expression Action Unit Detection via Enhanced LLM-Based Feature Fusion
Zhishu Liu, Kaishen Yuan, Bo Zhao +2
The detection of micro-expression Action Units (AUs) is a formidable challenge in affective computing, pivotal for decoding subtle, involuntary human emotions. While Large Language…
FEALLM: Advancing Facial Emotion Analysis in Multimodal Large Language Models with Emotional Synergy and Reasoning
Zhuozhao Hu, Kaishen Yuan, Xin Liu +5
Facial Emotion Analysis (FEA) plays a crucial role in visual affective computing, aiming to infer a person's emotional state based on facial data. Scientifically, facial expression…
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…
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…
DiffFAS: Face Anti-Spoofing via Generative Diffusion Models
Xinxu Ge, Xin Liu, Zitong Yu +4
Face anti-spoofing (FAS) plays a vital role in preventing face recognition (FR) systems from presentation attacks. Nowadays, FAS systems face the challenge of domain shift, impacti…
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…
From Recognition to Prediction: Leveraging Sequence Reasoning for Action Anticipation
Xin Liu, Chao Hao, Zitong Yu +2
The action anticipation task refers to predicting what action will happen based on observed videos, which requires the model to have a strong ability to summarize the present and t…
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…
GPT as Psychologist? Preliminary Evaluations for GPT-4V on Visual Affective Computing
Hao Lu, Xuesong Niu, Jiyao Wang +12
Multimodal large language models (MLLMs) are designed to process and integrate information from multiple sources, such as text, speech, images, and videos. Despite its success in l…
AUFormer: Vision Transformers are Parameter-Efficient Facial Action Unit Detectors
Kaishen Yuan, Zitong Yu, Xin Liu +3
Facial Action Units (AU) is a vital concept in the realm of affective computing, and AU detection has always been a hot research topic. Existing methods suffer from overfitting iss…
A Simple yet Effective Network based on Vision Transformer for Camouflaged Object and Salient Object Detection
Chao Hao, Zitong Yu, Xin Liu +3
Camouflaged object detection (COD) and salient object detection (SOD) are two distinct yet closely-related computer vision tasks widely studied during the past decades. Though shar…