240 citations · 1.3k across the 195 of their papers we have counts for
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Textured Mesh Saliency: Bridging Geometry and Texture for Human Perception in 3D Graphics
Kaiwei Zhang, Dandan Zhu, Xiongkuo Min +1
Textured meshes significantly enhance the realism and detail of objects by mapping intricate texture details onto the geometric structure of 3D models. This advancement is valuable…
Video Quality Assessment: A Comprehensive Survey
Qi Zheng, Yibo Fan, Leilei Huang +8
Video quality assessment (VQA) is an important processing task, aiming at predicting the quality of videos in a manner highly consistent with human judgments of perceived quality.…
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…
ESVQA: Perceptual Quality Assessment of Egocentric Spatial Videos
Xilei Zhu, Huiyu Duan, Liu Yang +4
With the rapid development of eXtended Reality (XR), egocentric spatial shooting and display technologies have further enhanced immersion and engagement for users, delivering more…
FineVQ: Fine-Grained User Generated Content Video Quality Assessment
Huiyu Duan, Qiang Hu, Jiarui Wang +8
The rapid growth of user-generated content (UGC) videos has produced an urgent need for effective video quality assessment (VQA) algorithms to monitor video quality and guide optim…
AIGV-Assessor: Benchmarking and Evaluating the Perceptual Quality of Text-to-Video Generation with LMM
Jiarui Wang, Huiyu Duan, Guangtao Zhai +2
The rapid advancement of large multimodal models (LMMs) has led to the rapid expansion of artificial intelligence generated videos (AIGVs), which highlights the pressing need for e…
MEMO-Bench: A Multiple Benchmark for Text-to-Image and Multimodal Large Language Models on Human Emotion Analysis
Yingjie Zhou, Zicheng Zhang, Jiezhang Cao +6
Artificial Intelligence (AI) has demonstrated significant capabilities in various fields, and in areas such as human-computer interaction (HCI), embodied intelligence, and the desi…
Grounding-IQA: Grounding Multimodal Language Model for Image Quality Assessment
Zheng Chen, Xun Zhang, Wenbo Li +7
The development of multimodal large language models (MLLMs) enables the evaluation of image quality through natural language descriptions. This advancement allows for more detailed…
Human-Activity AGV Quality Assessment: A Benchmark Dataset and an Objective Evaluation Metric
Zhichao Zhang, Wei Sun, Xinyue Li +9
AI-driven video generation techniques have made significant progress in recent years. However, AI-generated videos (AGVs) involving human activities often exhibit substantial visua…
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…
AIM 2024 Challenge on Video Super-Resolution Quality Assessment: Methods and Results
Ivan Molodetskikh, Artem Borisov, Dmitriy Vatolin +24
This paper presents the Video Super-Resolution (SR) Quality Assessment (QA) Challenge that was part of the Advances in Image Manipulation (AIM) workshop, held in conjunction with E…
AIM 2024 Challenge on Video Saliency Prediction: Methods and Results
Andrey Moskalenko, Alexey Bryncev, Dmitry Vatolin +30
This paper reviews the Challenge on Video Saliency Prediction at AIM 2024. The goal of the participants was to develop a method for predicting accurate saliency maps for the provid…
Explore the Hallucination on Low-level Perception for MLLMs
Yinan Sun, Zicheng Zhang, Haoning Wu +4
The rapid development of Multi-modality Large Language Models (MLLMs) has significantly influenced various aspects of industry and daily life, showcasing impressive capabilities in…
3DGCQA: A Quality Assessment Database for 3D AI-Generated Contents
Yingjie Zhou, Zicheng Zhang, Farong Wen +5
Although 3D generated content (3DGC) offers advantages in reducing production costs and accelerating design timelines, its quality often falls short when compared to 3D professiona…
Exploring Rich Subjective Quality Information for Image Quality Assessment in the Wild
Xiongkuo Min, Yixuan Gao, Yuqin Cao +4
Traditional in the wild image quality assessment (IQA) models are generally trained with the quality labels of mean opinion score (MOS), while missing the rich subjective quality i…
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…
Subjective and Objective Quality-of-Experience Evaluation Study for Live Video Streaming
Zehao Zhu, Wei Sun, Jun Jia +7
In recent years, live video streaming has gained widespread popularity across various social media platforms. Quality of experience (QoE), which reflects end-users' satisfaction an…
Towards Effective User Attribution for Latent Diffusion Models via Watermark-Informed Blending
Yongyang Pan, Xiaohong Liu, Siqi Luo +5
Rapid advancements in multimodal large language models have enabled the creation of hyper-realistic images from textual descriptions. However, these advancements also raise signifi…
Assessing UHD Image Quality from Aesthetics, Distortions, and Saliency
Wei Sun, Weixia Zhang, Yuqin Cao +6
UHD images, typically with resolutions equal to or higher than 4K, pose a significant challenge for efficient image quality assessment (IQA) algorithms, as adopting full-resolution…
LMM-VQA: Advancing Video Quality Assessment with Large Multimodal Models
Qihang Ge, Wei Sun, Yu Zhang +6
The explosive growth of videos on streaming media platforms has underscored the urgent need for effective video quality assessment (VQA) algorithms to monitor and perceptually opti…
SG-JND: Semantic-Guided Just Noticeable Distortion Predictor For Image Compression
Linhan Cao, Wei Sun, Xiongkuo Min +8
Just noticeable distortion (JND), representing the threshold of distortion in an image that is minimally perceptible to the human visual system (HVS), is crucial for image compress…
AIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results
Maksim Smirnov, Aleksandr Gushchin, Anastasia Antsiferova +29
Video quality assessment (VQA) is a crucial task in the development of video compression standards, as it directly impacts the viewer experience. This paper presents the results of…
How Does Audio Influence Visual Attention in Omnidirectional Videos? Database and Model
Yuxin Zhu, Huiyu Duan, Kaiwei Zhang +5
Understanding and predicting viewer attention in omnidirectional videos (ODVs) is crucial for enhancing user engagement in virtual and augmented reality applications. Although both…
UniProcessor: A Text-induced Unified Low-level Image Processor
Huiyu Duan, Xiongkuo Min, Sijing Wu +2
Image processing, including image restoration, image enhancement, etc., involves generating a high-quality clean image from a degraded input. Deep learning-based methods have shown…