43 citations · 171 across the 35 of their papers we have counts for
46 papers
A Comparative Study of Perceptual Quality Metrics for Audio-driven Talking Head Videos
Weixia Zhang, Chengguang Zhu, Jingnan Gao +3
The rapid advancement of Artificial Intelligence Generated Content (AIGC) technology has propelled audio-driven talking head generation, gaining considerable research attention for…
When No-Reference Image Quality Models Meet MAP Estimation in Diffusion Latents
Weixia Zhang, Dingquan Li, Guangtao Zhai +2
Contemporary no-reference image quality assessment (NR-IQA) models can effectively quantify perceived image quality, often achieving strong correlations with human perceptual score…
Few-Shot Class-Incremental Learning with Prior Knowledge
Wenhao Jiang, Duo Li, Menghan Hu +3
To tackle the issues of catastrophic forgetting and overfitting in few-shot class-incremental learning (FSCIL), previous work has primarily concentrated on preserving the memory of…
Uncertainty-aware Sampling for Long-tailed Semi-supervised Learning
Kuo Yang, Duo Li, Menghan Hu +3
For semi-supervised learning with imbalance classes, the long-tailed distribution of data will increase the model prediction bias toward dominant classes, undermining performance o…
A No-Reference Quality Assessment Method for Digital Human Head
Yingjie Zhou, Zicheng Zhang, Wei Sun +3
In recent years, digital humans have been widely applied in augmented/virtual reality (A/VR), where viewers are allowed to freely observe and interact with the volumetric content.…
Geometry-Aware Video Quality Assessment for Dynamic Digital Human
Zicheng Zhang, Yingjie Zhou, Wei Sun +2
Dynamic Digital Humans (DDHs) are 3D digital models that are animated using predefined motions and are inevitably bothered by noise/shift during the generation process and compress…