Text Guided Image Generation

Text-guided image generation focuses on creating or modifying images based on textual descriptions, aiming to bridge the gap between human language and visual content. Current research heavily utilizes diffusion models, often enhanced with techniques like multi-agent frameworks, mixture-of-experts controllers, and CLIP embeddings, to improve controllability, fidelity, and efficiency, including on resource-constrained devices. This field is significant for its potential applications in various domains, from creative content generation and industrial anomaly detection to advanced image editing and 3D scene synthesis, while also raising important considerations regarding copyright and ethical implications.