Video Quality Assessment
95 papers with code • 10 benchmarks • 12 datasets
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
These leaderboards are used to track progress in Video Quality Assessment
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Libraries
Use these libraries to find Video Quality Assessment models and implementationsDatasets
YouTube-UGC
LIVE-VQC
MSU SR-QA Dataset
MSU NR VQA Database
MSU FR VQA Database
LIVE-FB LSVQ
LIVE Livestream
Latest papers
Light-VQA+: A Video Quality Assessment Model for Exposure Correction with Vision-Language Guidance
Equally important to the VEC is the Video Quality Assessment (VQA).
AIS 2024 Challenge on Video Quality Assessment of User-Generated Content: Methods and Results
The performance of the top-5 submissions is reviewed and provided here as a survey of diverse deep models for efficient video quality assessment of user-generated content.
NTIRE 2024 Challenge on Short-form UGC Video Quality Assessment: Methods and Results
lixinustc/kvq-challenge-cvpr-ntire2024
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This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i. e., Kuaishou/Kwai Platform.
THQA: A Perceptual Quality Assessment Database for Talking Heads
In the realm of media technology, digital humans have gained prominence due to rapid advancements in computer technology.
Learned Scanpaths Aid Blind Panoramic Video Quality Assessment
Panoramic videos have the advantage of providing an immersive and interactive viewing experience.
Subjective-Aligned Dataset and Metric for Text-to-Video Quality Assessment
Based on T2VQA-DB, we propose a novel transformer-based model for subjective-aligned Text-to-Video Quality Assessment (T2VQA).
Modular Blind Video Quality Assessment
winwinwenwen77/modularbvqa
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Blind video quality assessment (BVQA) plays a pivotal role in evaluating and improving the viewing experience of end-users across a wide range of video-based platforms and services.
KVQ: Kwai Video Quality Assessment for Short-form Videos
lixinustc/kvq-challenge-cvpr-ntire2024
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Short-form UGC video platforms, like Kwai and TikTok, have been an emerging and irreplaceable mainstream media form, thriving on user-friendly engagement, and kaleidoscope creation, etc.
Scaling and Masking: A New Paradigm of Data Sampling for Image and Video Quality Assessment
sissuire/sama
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In this work, instead of stacking up models, a more elegant data sampling method (named as SAMA, scaling and masking) is explored, which compacts both the local and global content in a regular input size.
Q-Align: Teaching LMMs for Visual Scoring via Discrete Text-Defined Levels
q-future/q-align
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The explosion of visual content available online underscores the requirement for an accurate machine assessor to robustly evaluate scores across diverse types of visual contents.
