7 citations · 7 across the 8 of their papers we have counts for
9 papers
AGIDefect-4K: A Richly Annotated Dataset for AI-Generated Image Defect Detection, Localization and Explanation
Xiangfei Sheng, Weidong Zou, Tianjiao Gu +3
Generative AI can now produce highly realistic images, yet current models still exhibit subtle but critical defects that undermine their reliability. While existing AI-generated im…
Personalized Image Aesthetic Assessment via Preference-rich Sample Mining and Cohort Merging
Zhichao Yang, Tianjiao Gu, Zhixianhe Zhang +3
Personalized Image Aesthetic Assessment (PIAA) aims to predict aesthetic ratings of images that vary across individuals. The aesthetic preferences manifest to different extents acr…
Fine-grained Image Aesthetic Assessment: Learning Discriminative Scores from Relative Ranks
Zhichao Yang, Jianjie Wang, Zhixianhe Zhang +4
Image aesthetic assessment (IAA) has extensive applications in content creation, album management, and recommendation systems, etc. In such applications, it is commonly needed to p…
LongT2IBench: A Benchmark for Evaluating Long Text-to-Image Generation with Graph-structured Annotations
Zhichao Yang, Tianjiao Gu, Jianjie Wang +4
The increasing popularity of long Text-to-Image (T2I) generation has created an urgent need for automatic and interpretable models that can evaluate the image-text alignment in lon…
TuningIQA: Fine-Grained Blind Image Quality Assessment for Livestreaming Camera Tuning
Xiangfei Sheng, Zhichao Duan, Xiaofeng Pan +4
Livestreaming has become increasingly prevalent in modern visual communication, where automatic camera quality tuning is essential for delivering superior user Quality of Experienc…
Fine-grained Image Quality Assessment for Perceptual Image Restoration
Xiangfei Sheng, Xiaofeng Pan, Zhichao Yang +2
Recent years have witnessed remarkable achievements in perceptual image restoration (IR), creating an urgent demand for accurate image quality assessment (IQA), which is essential…
Language-Guided Visual Perception Disentanglement for Image Quality Assessment and Conditional Image Generation
Zhichao Yang, Leida Li, Pengfei Chen +2
Contrastive vision-language models, such as CLIP, have demonstrated excellent zero-shot capability across semantic recognition tasks, mainly attributed to the training on a large-s…
AesExpert: Towards Multi-modality Foundation Model for Image Aesthetics Perception
Yipo Huang, Xiangfei Sheng, Zhichao Yang +6
The highly abstract nature of image aesthetics perception (IAP) poses significant challenge for current multimodal large language models (MLLMs). The lack of human-annotated multi-…
AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception
Yipo Huang, Quan Yuan, Xiangfei Sheng +6
With collective endeavors, multimodal large language models (MLLMs) are undergoing a flourishing development. However, their performances on image aesthetics perception remain inde…