33 citations · 93 across the 56 of their papers we have counts for
19 papers · 1 filter
VQA: Visual Question Answering for Video Quality Assessment
Ziheng Jia, Zicheng Zhang, Jiaying Qian +7
The advent and proliferation of large multi-modal models (LMMs) have introduced new paradigms to computer vision, transforming various tasks into a unified visual question answerin…
Embodied Image Quality Assessment for Robotic Intelligence
Jianbo Zhang, Chunyi Li, Jie Hao +5
Image Quality Assessment (IQA) of User-Generated Content (UGC) is a critical technique for human Quality of Experience (QoE). However, does the the image quality of Robot-Generated…
R-Bench: Are your Large Multimodal Model Robust to Real-world Corruptions?
Chunyi Li, Jianbo Zhang, Zicheng Zhang +8
The outstanding performance of Large Multimodal Models (LMMs) has made them widely applied in vision-related tasks. However, various corruptions in the real world mean that images…
Q-Bench-Video: Benchmarking the Video Quality Understanding of LMMs
Zicheng Zhang, Ziheng Jia, Haoning Wu +8
With the rising interest in research on Large Multi-modal Models (LMMs) for video understanding, many studies have emphasized general video comprehension capabilities, neglecting t…
Quality Assessment in the Era of Large Models: A Survey
Zicheng Zhang, Yingjie Zhou, Chunyi Li +3
Quality assessment, which evaluates the visual quality level of multimedia experiences, has garnered significant attention from researchers and has evolved substantially through de…
Benchmarking Multi-dimensional AIGC Video Quality Assessment: A Dataset and Unified Model
Zhichao Zhang, Wei Sun, Xinyue Li +9
In recent years, artificial intelligence (AI)-driven video generation has gained significant attention. Consequently, there is a growing need for accurate video quality assessment…
HazeCLIP: Towards Language Guided Real-World Image Dehazing
Ruiyi Wang, Wenhao Li, Xiaohong Liu +4
Existing methods have achieved remarkable performance in image dehazing, particularly on synthetic datasets. However, they often struggle with real-world hazy images due to domain…
CMC-Bench: Towards a New Paradigm of Visual Signal Compression
Chunyi Li, Xiele Wu, Haoning Wu +7
Ultra-low bitrate image compression is a challenging and demanding topic. With the development of Large Multimodal Models (LMMs), a Cross Modality Compression (CMC) paradigm of Ima…
A-Bench: Are LMMs Masters at Evaluating AI-generated Images?
Zicheng Zhang, Haoning Wu, Chunyi Li +7
How to accurately and efficiently assess AI-generated images (AIGIs) remains a critical challenge for generative models. Given the high costs and extensive time commitments require…
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance
Xunchu Zhou, Xiaohong Liu, Yunlong Dong +6
Recently, User-Generated Content (UGC) videos have gained popularity in our daily lives. However, UGC videos often suffer from poor exposure due to the limitations of photographic…
NTIRE 2024 Quality Assessment of AI-Generated Content Challenge
Xiaohong Liu, Xiongkuo Min, Guangtao Zhai +111
This paper reports on the NTIRE 2024 Quality Assessment of AI-Generated Content Challenge, which will be held in conjunction with the New Trends in Image Restoration and Enhancemen…
G-Refine: A General Quality Refiner for Text-to-Image Generation
Chunyi Li, Haoning Wu, Hongkun Hao +7
With the evolution of Text-to-Image (T2I) models, the quality defects of AI-Generated Images (AIGIs) pose a significant barrier to their widespread adoption. In terms of both perce…
AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results
Marcos V. Conde, Saman Zadtootaghaj, Nabajeet Barman +33
This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge, focused on User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based method…
AIGIQA-20K: A Large Database for AI-Generated Image Quality Assessment
Chunyi Li, Tengchuan Kou, Yixuan Gao +10
With the rapid advancements in AI-Generated Content (AIGC), AI-Generated Images (AIGIs) have been widely applied in entertainment, education, and social media. However, due to the…
LMM-PCQA: Assisting Point Cloud Quality Assessment with LMM
Zicheng Zhang, Haoning Wu, Yingjie Zhou +7
Although large multi-modality models (LMMs) have seen extensive exploration and application in various quality assessment studies, their integration into Point Cloud Quality Assess…
Towards Open-ended Visual Quality Comparison
Haoning Wu, Hanwei Zhu, Zicheng Zhang +11
Comparative settings (e.g. pairwise choice, listwise ranking) have been adopted by a wide range of subjective studies for image quality assessment (IQA), as it inherently standardi…
Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment
Tengchuan Kou, Xiaohong Liu, Zicheng Zhang +5
With the rapid development of generative models, Artificial Intelligence-Generated Contents (AIGC) have exponentially increased in daily lives. Among them, Text-to-Video (T2V) gene…
MISC: Ultra-low Bitrate Image Semantic Compression Driven by Large Multimodal Model
Chunyi Li, Guo Lu, Donghui Feng +6
With the evolution of storage and communication protocols, ultra-low bitrate image compression has become a highly demanding topic. However, existing compression algorithms must sa…
Q-Refine: A Perceptual Quality Refiner for AI-Generated Image
Chunyi Li, Haoning Wu, Zicheng Zhang +7
With the rapid evolution of the Text-to-Image (T2I) model in recent years, their unsatisfactory generation result has become a challenge. However, uniformly refining AI-Generated I…