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Found 15 papers, 6 papers with code
Direct Optimisation of $\boldsymbolλ$ for HDR Content Adaptive Transcoding in AV1
Since the adoption of VP9 by Netflix in 2016, royalty-free coding standards continued to gain prominence through the activities of the AOMedia consortium.
CONVIQT: Contrastive Video Quality Estimator
Perceptual video quality assessment (VQA) is an integral component of many streaming and video sharing platforms.
Ranked #1 on
Video Quality Assessment
on LIVE-ETRI
(using extra training data)
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions
We consider the problem of capturing distortions arising from changes in frame rate as part of Video Quality Assessment (VQA).
Perceptual Quality Assessment of UGC Gaming Videos
In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased.
Subjective and Objective Analysis of Streamed Gaming Videos
A number of studies have been directed towards understanding the perceptual characteristics of professionally generated gaming videos arising in gaming video streaming, online gaming, and cloud gaming.
Image Quality Assessment using Contrastive Learning
We consider the problem of obtaining image quality representations in a self-supervised manner.
Ranked #2 on
Video Quality Assessment
on LIVE-ETRI
(using extra training data)
High Frame Rate Video Quality Assessment using VMAF and Entropic Differences
In this work we address the problem of frame rate dependent Video Quality Assessment (VQA) when the videos to be compared have different frame rate and compression factor.
Ranked #2 on
Video Quality Assessment
on LIVE-YT-HFR
Rich Features for Perceptual Quality Assessment of UGC Videos
Besides the subjective ratings and content labels of the dataset, we also propose a DNN-based framework to thoroughly analyze importance of content, technical quality, and compression level in perceptual quality.
Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models
Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus.
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
However, these models are either incapable or inefficient for predicting the quality of complex and diverse UGC videos in practical applications.
Ranked #4 on
Video Quality Assessment
on LIVE Livestream
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction
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.
Ranked #1 on
Video Quality Assessment
on LIVE-YT-HFR
Subjective and Objective Quality Assessment of High Frame Rate Videos
We also conducted a holistic evaluation of existing state-of-the-art Full and No-Reference video quality algorithms, and statistically benchmarked their performance on the new database.
Capturing Video Frame Rate Variations via Entropic Differencing
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 experiences to consumers.
Ranked #3 on
Video Quality Assessment
on LIVE-YT-HFR
UGC-VQA: Benchmarking Blind Video Quality Assessment for User Generated Content
Recent years have witnessed an explosion of user-generated content (UGC) videos shared and streamed over the Internet, thanks to the evolution of affordable and reliable consumer capture devices, and the tremendous popularity of social media platforms.
Ranked #11 on
Video Quality Assessment
on YouTube-UGC
A Comparative Evaluation of Temporal Pooling Methods for Blind Video Quality Assessment
Many objective video quality assessment (VQA) algorithms include a key step of temporal pooling of frame-level quality scores.
