Video generation has witnessed significant advancements yet evaluating these models
remains a challenge. A comprehensive evaluation benchmark for video generation is …

This paper reviews the AIS 2024 Video Quality Assessment (VQA) Challenge focused on
User-Generated Content (UGC). The aim of this challenge is to gather deep learning-based …

Multi-modality large language models (MLLMs) as represented by GPT-4V have introduced
a paradigm shift for visual perception and understanding tasks that a variety of abilities can …

The rapid increase in user-generated-content (UGC) videos calls for the development of
effective video quality assessment (VQA) algorithms. However, the objective of the UGC …

User-generated content (UGC) live videos are often bothered by various distortions during
capture procedures and thus exhibit diverse visual qualities. Such source videos are further …

The explosion of visual content available online underscores the requirement for an
accurate machine assessor to robustly evaluate scores across diverse types of visual …

Compared with spatial counterparts, temporal relationships between frames and their
influences on video quality assessment (VQA) are still relatively under-studied in existing …

This paper reports on the NTIRE 2023 Quality Assessment of Video Enhancement
Challenge, which will be held in conjunction with the New Trends in Image Restoration and …

Short-form UGC video platforms like Kwai and TikTok have been an emerging and
irreplaceable mainstream media form thriving on user-friendly engagement and …

Comparative settings (eg pairwise choice, listwise ranking) have been adopted by a wide
range of subjective studies for image quality assessment (IQA), as it inherently standardizes …