Image-Generation-CoT introduces a novel approach to text-to-image generation using Chain-of-Thought (CoT) prompting. By breaking down complex prompts into structured reasoning steps, the model enhances coherence, detail, and semantic alignment in generated images. This method aims to bridge the gap between natural language understanding and high-fidelity visual generation.
Key Features
Chain-of-Thought (CoT) reasoning to interpret complex prompts
Step-by-step visual synthesis for improved image quality
Supports multi-stage generation pipelines
Enhances alignment between prompt semantics and visual output
Evaluation on compositional and reasoning-heavy benchmarks
Modular design for easy integration with various diffusion models
Focus on grounded, interpretable image generation
Research-grade implementation for advanced AI applications
Android DevHub
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