activity
20202022
most citedFAVER: Blind Quality Prediction of Variable Frame Rate Videos

6 citations · 13 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV20222 cited

Making Video Quality Assessment Models Sensitive to Frame Rate Distortions

Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2

We consider the problem of capturing distortions arising from changes in frame rate as part of Video Quality Assessment (VQA). Variable frame rate (VFR) videos have become much mor…

eess.IV20226 cited

FAVER: Blind Quality Prediction of Variable Frame Rate Videos

Qi Zheng, Zhengzhong Tu, Pavan C. Madhusudana +3

Video quality assessment (VQA) remains an important and challenging problem that affects many applications at the widest scales. Recent advances in mobile devices and cloud computi…

cs.MM20215 cited

High Frame Rate Video Quality Assessment using VMAF and Entropic Differences

Pavan C Madhusudana, Neil Birkbeck, Yilin Wang +2

The popularity of streaming videos with live, high-action content has led to an increased interest in High Frame Rate (HFR) videos. In this work we address the problem of frame rat…

cs.MM2020

ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction

Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2

We consider the problem of conducting frame rate dependent video quality assessment (VQA) on videos of diverse frame rates, including high frame rate (HFR) videos. More generally,…

cs.MM2020

Capturing Video Frame Rate Variations via Entropic Differencing

Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2

High frame rate videos are increasingly getting popular in recent years, driven by the strong requirements of the entertainment and streaming industries to provide high quality of…