Garment Generation

Garment generation research focuses on automatically creating realistic 3D clothing and 2D clothing images from various inputs like text descriptions, sketches, or images. Current efforts leverage advanced generative models, including diffusion models and variational autoencoders, often incorporating techniques like Gaussian splatting, multi-level corrections, and control nets to improve detail, consistency, and control over garment features such as texture and geometry. This field is significant for its potential to revolutionize fashion design, virtual try-on technologies, and the creation of digital humans, streamlining workflows and enabling new creative possibilities.