43 citations · 88 across the 10 of their papers we have counts for
10 papers
AUHead: Realistic Emotional Talking Head Generation via Action Units Control
Jiayi Lyu, Leigang Qu, Wenjing Zhang +6
Realistic talking-head video generation is critical for virtual avatars, film production, and interactive systems. Current methods struggle with nuanced emotional expressions due t…
Towards Unified Facial Action Unit Recognition Framework by Large Language Models
Guohong Hu, Xing Lan, Hanyu Jiang +2
Facial Action Units (AUs) are of great significance in the realm of affective computing. In this paper, we propose AU-LLaVA, the first unified AU recognition framework based on the…
FoodSAM: Any Food Segmentation
Xing Lan, Jiayi Lyu, Hanyu Jiang +4
In this paper, we explore the zero-shot capability of the Segment Anything Model (SAM) for food image segmentation. To address the lack of class-specific information in SAM-generat…
K-Space-Aware Cross-Modality Score for Synthesized Neuroimage Quality Assessment
Guoyang Xie, Jinbao Wang, Yawen Huang +4
The problem of how to assess cross-modality medical image synthesis has been largely unexplored. The most used measures like PSNR and SSIM focus on analyzing the structural feature…
IM-IAD: Industrial Image Anomaly Detection Benchmark in Manufacturing
Guoyang Xie, Jinbao Wang, Jiaqi Liu +5
Image anomaly detection (IAD) is an emerging and vital computer vision task in industrial manufacturing (IM). Recently, many advanced algorithms have been reported, but their perfo…
Cross-Modality Neuroimage Synthesis: A Survey
Guoyang Xie, Yawen Huang, Jinbao Wang +4
Multi-modality imaging improves disease diagnosis and reveals distinct deviations in tissues with anatomical properties. The existence of completely aligned and paired multi-modali…
FedMed-GAN: Federated Domain Translation on Unsupervised Cross-Modality Brain Image Synthesis
Jinbao Wang, Guoyang Xie, Yawen Huang +4
Utilizing multi-modal neuroimaging data has been proved to be effective to investigate human cognitive activities and certain pathologies. However, it is not practical to obtain th…
FEAFA+: An Extended Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
Wei Gan, Jian Xue, Ke Lu +3
Nearly all existing Facial Action Coding System-based datasets that include facial action unit (AU) intensity information annotate the intensity values hierarchically using A--E le…
Tiny Adversarial Mulit-Objective Oneshot Neural Architecture Search
Guoyang Xie, Jinbao Wang, Guo Yu +2
Due to limited computational cost and energy consumption, most neural network models deployed in mobile devices are tiny. However, tiny neural networks are commonly very vulnerable…
FEAFA: A Well-Annotated Dataset for Facial Expression Analysis and 3D Facial Animation
Yanfu Yan, Ke Lu, Jian Xue +2
Facial expression analysis based on machine learning requires large number of well-annotated data to reflect different changes in facial motion. Publicly available datasets truly h…