93 citations · 139 across the 11 of their papers we have counts for
11 papers
ActFER: Agentic Facial Expression Recognition via Active Tool-Augmented Visual Reasoning
Shifeng Liu, Zhengye Zhang, Sirui Zhao +7
Recent advances in Multimodal Large Language Models (MLLMs) have created new opportunities for facial expression recognition (FER), moving it beyond pure label prediction toward re…
SyncBreaker:Stage-Aware Multimodal Adversarial Attacks on Audio-Driven Talking Head Generation
Wenli Zhang, Xianglong Shi, Sirui Zhao +5
Diffusion-based audio-driven talking-head generation enables realistic portrait animation, but also introduces risks of misuse, such as fraud and misinformation. Existing protectio…
Bind-Your-Avatar: Multi-Talking-Character Video Generation with Dynamic 3D-mask-based Embedding Router
Yubo Huang, Weiqiang Wang, Sirui Zhao +3
Recent years have witnessed remarkable advances in audio-driven talking head generation. However, existing approaches predominantly focus on single-character scenarios. While some…
MERba: Multi-Receptive Field MambaVision for Micro-Expression Recognition
Xinglong Mao, Shifeng Liu, Sirui Zhao +4
Micro-expressions (MEs) are brief, involuntary facial movements that reveal genuine emotions, offering valuable insights for psychological assessment and criminal investigations. D…
MER-CLIP: AU-Guided Vision-Language Alignment for Micro-Expression Recognition
Shifeng Liu, Xinglong Mao, Sirui Zhao +3
As a critical psychological stress response, micro-expressions (MEs) are fleeting and subtle facial movements revealing genuine emotions. Automatic ME recognition (MER) holds valua…
MELLM: A Flow-Guided Large Language Model for Micro-Expression Understanding
Sirui Zhao, Zhengye Zhang, Shifeng Liu +5
Micro-expressions (MEs), brief and low-intensity facial movements revealing concealed emotions, are crucial for affective computing. Despite notable progress in ME recognition, exi…
Sparrow: Data-Efficient Video-LLM with Text-to-Image Augmentation
Shukang Yin, Chaoyou Fu, Sirui Zhao +7
Recent years have seen the success of Multimodal Large Language Models (MLLMs) in the domain of vision understanding. The success of these models can largely be attributed to the d…
From a Social Cognitive Perspective: Context-aware Visual Social Relationship Recognition
Shiwei Wu, Chao Zhang, Joya Chen +4
People's social relationships are often manifested through their surroundings, with certain objects or interactions acting as symbols for specific relationships, e.g., wedding ring…
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
Chaoyou Fu, Yuhan Dai, Yongdong Luo +18
In the quest for artificial general intelligence, Multi-modal Large Language Models (MLLMs) have emerged as a focal point in recent advancements. However, the predominant focus rem…
Woodpecker: Hallucination Correction for Multimodal Large Language Models
Shukang Yin, Chaoyou Fu, Sirui Zhao +7
Hallucination is a big shadow hanging over the rapidly evolving Multimodal Large Language Models (MLLMs), referring to the phenomenon that the generated text is inconsistent with t…
DFME: A New Benchmark for Dynamic Facial Micro-expression Recognition
Sirui Zhao, Huaying Tang, Xinglong Mao +5
One of the most important subconscious reactions, micro-expression (ME), is a spontaneous, subtle, and transient facial expression that reveals human beings' genuine emotion. There…