Kolors: Effective Training of Diffusion Model for Photorealistic Text-to-Image Synthesis

📖 Introduction Kolors is a large-scale text-to-image generation model based on latent diffusion, developed by the Kuaishou Kolors team. Trained on billions of text-image pairs, Kolors exhibits significant advantages over both open-source and closed-source models in visual quality, complex semantic accuracy, and text rendering for both Chinese and English characters. Furthermore, Kolors supports both Chinese and English inputs, demonstrating strong performance in understanding and generating Chinese-specific content. For more details, please refer to this technical report.

📊 Evaluation We have collected a comprehensive text-to-image evaluation dataset named KolorsPrompts to compare Kolors with other state-of-the-art open models and closed-source models. KolorsPrompts includes over 1,000 prompts across 14 catagories and 12 evaluation dimensions. The evaluation process incorporates both human and machine assessments. In relevant benchmark evaluations, Kolors demonstrated highly competitive performance, achieving industry-leading standards.

Human Assessment For the human evaluation, we invited 50 imagery experts to conduct comparative evaluations of the results generated by different models. The experts rated the generated images based on three criteria: visual appeal, text faithfulness, and overall satisfaction. In the evaluation, Kolors achieved the highest overall satisfaction score and significantly led in visual appeal compared to other models.

Machine Assessment We used MPS (Multi-dimensional Human Preference Score) on KolorsPrompts as the evaluation metric for machine assessment. Kolors achieved the highest MPS score, which is consistent with the results of the human evaluations.

Models Overall MPS Adobe-Firefly 8.5 Stable Diffusion 3 8.9 DALL-E 3 9.0 Midjourney-v5 9.4 Playground-v2.5 9.8 Midjourney-v6 10.2 Kolors 10.3