Exploring AIGC Video Quality: A Focus on Visual Harmony, Video-Text Consistency and Domain Distribution Gap

Understand

The recent advancements in Text-to-Video Artificial Intelligence Generated Content (AIGC) have been remarkable.

• Compared with traditional videos, the assessment of AIGC videos encounters various challenges: visual inconsistency that defy common sense, discrepancies between content and the textual prompt, and distribution gap between various generative models, etc.
• Target at these challenges, in this work, we categorize the assessment of AIGC video quality into three dimensions: visual harmony, video-text consistency, and domain distribution gap.
• For each dimension, we design specific modules to provide a comprehensive quality assessment of AIGC videos.