The field of virtual try-on and fashion generation is rapidly evolving, with a focus on improving the accuracy and personalization of garment reconstruction and outfit generation. Recent developments have led to the creation of more sophisticated models that can capture fine geometric details and ensure physical plausibility. The use of diffusion models and latent diffusion frameworks has shown promise in enhancing the quality of generated garments and outfits. Additionally, there is a growing emphasis on controllable fashion design, allowing for precise control over silhouette, color, and logo placement. Noteworthy papers include:

• Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates, which presents a novel method for high-fidelity 3D garment reconstruction from single images.
• IMAGGarment-1: Fine-Grained Garment Generation for Controllable Fashion Design, which enables high-fidelity garment synthesis with precise control over design elements.