Ai Generated Image Quality Assessment

AI-generated image quality assessment (AGIQA) focuses on developing methods to automatically evaluate the perceptual quality of images created by artificial intelligence, aiming to align machine judgments with human preferences. Current research heavily utilizes multimodal models, often incorporating CLIP (Contrastive Language-Image Pre-training) and leveraging textual prompts alongside visual features to better capture the nuances of AI-generated content, including aspects like visual harmony, authenticity, and text-to-image alignment. This field is crucial for improving the quality of AI image generation and for establishing objective benchmarks to guide the development and refinement of generative models, ultimately impacting various applications from entertainment to advertising.