321 citations · 1.8k across the 90 of their papers we have counts for
90 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…
Q-Bench: A Benchmark for General-Purpose Foundation Models on Low-level Vision
Haoning Wu, Zicheng Zhang, Erli Zhang +8
The rapid evolution of Multi-modality Large Language Models (MLLMs) has catalyzed a shift in computer vision from specialized models to general-purpose foundation models. Neverthel…
AccFlow: Backward Accumulation for Long-Range Optical Flow
Guangyang Wu, Xiaohong Liu, Kunming Luo +6
Recent deep learning-based optical flow estimators have exhibited impressive performance in generating local flows between consecutive frames. However, the estimation of long-range…
StableVQA: A Deep No-Reference Quality Assessment Model for Video Stability
Tengchuan Kou, Xiaohong Liu, Wei Sun +4
Video shakiness is an unpleasant distortion of User Generated Content (UGC) videos, which is usually caused by the unstable hold of cameras. In recent years, many video stabilizati…
RAWIW: RAW Image Watermarking Robust to ISP Pipeline
Kang Fu, Xiaohong Liu, Jun Jia +4
Invisible image watermarking is essential for image copyright protection. Compared to RGB images, RAW format images use a higher dynamic range to capture the radiometric characteri…
Perceptual Quality Assessment of Omnidirectional Audio-visual Signals
Xilei Zhu, Huiyu Duan, Yuqin Cao +6
Omnidirectional videos (ODVs) play an increasingly important role in the application fields of medical, education, advertising, tourism, etc. Assessing the quality of ODVs is signi…
NTIRE 2023 Quality Assessment of Video Enhancement Challenge
Xiaohong Liu, Xiongkuo Min, Wei Sun +69
This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancement W…
AIGCIQA2023: A Large-scale Image Quality Assessment Database for AI Generated Images: from the Perspectives of Quality, Authenticity and Correspondence
Jiarui Wang, Huiyu Duan, Jing Liu +3
In this paper, in order to get a better understanding of the human visual preferences for AIGIs, a large-scale IQA database for AIGC is established, which is named as AIGCIQA2023.…
Advancing Zero-Shot Digital Human Quality Assessment through Text-Prompted Evaluation
Zicheng Zhang, Wei Sun, Yingjie Zhou +6
Digital humans have witnessed extensive applications in various domains, necessitating related quality assessment studies. However, there is a lack of comprehensive digital human q…
Analysis of Video Quality Datasets via Design of Minimalistic Video Quality Models
Wei Sun, Wen Wen, Xiongkuo Min +3
Blind video quality assessment (BVQA) plays an indispensable role in monitoring and improving the end-users' viewing experience in various real-world video-enabled media applicatio…
AGIQA-3K: An Open Database for AI-Generated Image Quality Assessment
Chunyi Li, Zicheng Zhang, Haoning Wu +5
With the rapid advancements of the text-to-image generative model, AI-generated images (AGIs) have been widely applied to entertainment, education, social media, etc. However, cons…
GMS-3DQA: Projection-based Grid Mini-patch Sampling for 3D Model Quality Assessment
Zicheng Zhang, Wei Sun, Houning Wu +5
Nowadays, most 3D model quality assessment (3DQA) methods have been aimed at improving performance. However, little attention has been paid to the computational cost and inference…
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancement
Yunlong Dong, Xiaohong Liu, Yixuan Gao +3
Recently, Users Generated Content (UGC) videos becomes ubiquitous in our daily lives. However, due to the limitations of photographic equipments and techniques, UGC videos often co…
MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videos
Zicheng Zhang, Wei Wu, Wei Sun +5
User-generated content (UGC) live videos are often bothered by various distortions during capture procedures and thus exhibit diverse visual qualities. Such source videos are furth…
Blind Image Quality Assessment via Vision-Language Correspondence: A Multitask Learning Perspective
Weixia Zhang, Guangtao Zhai, Ying Wei +2
We aim at advancing blind image quality assessment (BIQA), which predicts the human perception of image quality without any reference information. We develop a general and automate…
XGC-VQA: A unified video quality assessment model for User, Professionally, and Occupationally-Generated Content
Xinhui Huang, Chunyi Li, Abdelhak Bentaleb +2
With the rapid growth of Internet video data amounts and types, a unified Video Quality Assessment (VQA) is needed to inspire video communication with perceptual quality. To meet t…
A Perceptual Quality Assessment Exploration for AIGC Images
Zicheng Zhang, Chunyi Li, Wei Sun +3
\underline{AI} \underline{G}enerated \underline{C}ontent (\textbf{AIGC}) has gained widespread attention with the increasing efficiency of deep learning in content creation. AIGC,…
VDPVE: VQA Dataset for Perceptual Video Enhancement
Yixuan Gao, Yuqin Cao, Tengchuan Kou +5
Recently, many video enhancement methods have been proposed to improve video quality from different aspects such as color, brightness, contrast, and stability. Therefore, how to ev…
CASP-Net: Rethinking Video Saliency Prediction from an Audio-VisualConsistency Perceptual Perspective
Junwen Xiong, Ganglai Wang, Peng Zhang +3
Incorporating the audio stream enables Video Saliency Prediction (VSP) to imitate the selective attention mechanism of human brain. By focusing on the benefits of joint auditory an…