Results 11 to 20 of about 11,643,007 (169)
Light-VQA: A Multi-Dimensional Quality Assessment Model for Low-Light Video Enhancement [PDF]
Proceedings of the 31st ACM International Conference on Multimedia, 2023 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 contain various degradations, in which one of the most visually unfavorable effects is the underexposure.
Yunlong Dong +5 more
core +5 more sources
MD-VQA: Multi-Dimensional Quality Assessment for UGC Live Videos [PDF]
2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023 Accepted to ...
Zicheng Zhang +7 more
core +4 more sources
Perceptual video quality assessment: the journey continues! [PDF]
Frontiers in Signal Processing, 2023 Perceptual Video Quality Assessment (VQA) is one of the most fundamental and challenging problems in the field of Video Engineering. Along with video compression, it has become one of two dominant theoretical and algorithmic technologies in television ...
Avinab Saha +7 more
doaj +2 more sources
2023 IEEE International Conference on Multimedia and Expo Workshops (ICMEW), 2023 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 the real-time and universal requirements in providing such inspiration, this study proposes a VQA model from a classification of User Generated Content (UGC), Professionally ...
Xinhui Huang +4 more
openaire +5 more sources
An Efficient Method for No-Reference Video Quality Assessment [PDF]
Journal of Imaging, 2021 Methods for No-Reference Video Quality Assessment (NR-VQA) of consumer-produced video content are largely investigated due to the spread of databases containing videos affected by natural distortions.
Mirko Agarla +2 more
doaj +2 more sources
A Perspective on Quality Evaluation for AI-Generated Videos [PDF]
SensorsRecent breakthroughs in AI-generated content (AIGC) have transformed video creation, empowering systems to translate text, images, or audio into visually compelling stories.
Zhichao Zhang, Wei Sun, Guangtao Zhai
doaj +2 more sources
Factors impacting human-perceived visual quality on television displays [PDF]
Frontiers in NeuroscienceThere is a growing interest in understanding the factors that influence a user's perception and preferences for video quality. This study specifically focuses on how various factors, including video content, display settings, viewer characteristics, and ...
Eddie Pei +3 more
doaj +2 more sources
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance
International Journal of Computer VisionRecently, 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 equipment and techniques. Therefore, Video Exposure Correction (VEC) algorithms have been proposed, Low-Light Video Enhancement (LLVE) and Over-Exposed Video Recovery (OEVR ...
Xunchu Zhou +8 more
openaire +4 more sources
ReLaX-VQA: Residual Fragment and Layer Stack Extraction for Enhancing Video Quality Assessment [PDF]
CoRRWith the rapid growth of User-Generated Content (UGC) exchanged between users and sharing platforms, the need for video quality assessment in the wild is increasingly evident. UGC is typically acquired using consumer devices and undergoes multiple rounds of compression (transcoding) before reaching the end user.
Wang, Xinyi +2 more
core +5 more sources
Objective Underwater Video Quality Assessment Model via Two-Stream Networks [PDF]
Jisuanji kexue yu tansuo, 2023 Underwater videos often suffer from quality degradation. On the one hand, the exponential attenuation of the natural light in water media leads to the loss of underwater video quality.
SONG Wei, XIAO Yi, DU Yanling, ZHANG Minghua
doaj +1 more source