6 citations · 14 across the 5 of their papers we have counts for
4 papers · 1 filter
MVAD: A Multiple Visual Artifact Detector for Video Streaming
Chen Feng, Duolikun Danier, Fan Zhang +3
Visual artifacts are often introduced into streamed video content, due to prevailing conditions during content production and delivery. Since these can degrade the quality of the u…
RMT-BVQA: Recurrent Memory Transformer-based Blind Video Quality Assessment for Enhanced Video Content
Tianhao Peng, Chen Feng, Duolikun Danier +4
With recent advances in deep learning, numerous algorithms have been developed to enhance video quality, reduce visual artifacts, and improve perceptual quality. However, little re…
RankDVQA-mini: Knowledge Distillation-Driven Deep Video Quality Assessment
Chen Feng, Duolikun Danier, Haoran Wang +4
Deep learning-based video quality assessment (deep VQA) has demonstrated significant potential in surpassing conventional metrics, with promising improvements in terms of correlati…
A Subjective Study on Videos at Various Bit Depths
Alex Mackin, Di Ma, Fan Zhang +1
Bit depth adaptation, where the bit depth of a video sequence is reduced before transmission and up-sampled during display, can potentially reduce data rates with limited impact on…