most citedAIM 2024 Challenge on Compressed Video Quality Assessment: Methods and Results

7 citations · 13 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025★ 1 cited

Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videos

Qi Zheng, Li-Heng Chen, Chenlong He +6

Although there have been notable advancements in video compression technologies in recent years, banding artifacts remain a serious issue affecting the quality of compressed videos…

cs.CV2024

Unicorn: Unified Neural Image Compression with One Number Reconstruction

Qi Zheng, Haozhi Wang, Zihao Liu +8

Prevalent lossy image compression schemes can be divided into: 1) explicit image compression (EIC), including traditional standards and neural end-to-end algorithms; 2) implicit im…

eess.IV2024★ 5 cited

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.…

eess.IV2024★ 7 cited

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…

cs.CV2024

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…