Video Quality Assessment

18 benchmarks216 papers

Video Quality Assessment is a computer vision task aiming to mimic video-based human subjective perception. The goal is to produce a mos score, where higher score indicates better perceptual quality. Some well-known benchmarks for this task are KoNViD-1k, LIVE-VQC, YouTube-UGC and LSVQ. SROCC/PLCC/RMSE are usually used to evaluate the performance of different models.

Benchmarks

Video Quality Assessment on MSU SR-QA Dataset

Video Quality Assessment on KoNViD-1k

Video Quality Assessment on MSU NR VQA Database

Video Quality Assessment on LIVE-VQC

Video Quality Assessment on MSU FR VQA Database

Video Quality Assessment on YouTube-UGC

Video Quality Assessment on LIVE-FB LSVQ

Video Quality Assessment on LIVE-ETRI

Video Quality Assessment on LIVE Livestream

Video Quality Assessment on LIVE-YT-HFR