Multi Layered

Multi-layered garment modeling focuses on realistically representing and animating clothing with multiple layers, addressing limitations of previous single-layer approaches. Current research employs various techniques, including diffusion models, implicit surface representations (like signed distance functions), and graph neural networks (GNNs) to model complex interactions between garment layers and the human body. This work is significant for advancing virtual try-on technologies, improving the realism of 3D character animation, and enabling more accurate simulations of clothing behavior in various contexts. The development of large-scale datasets specifically designed for multi-layered garment research is also a key trend, facilitating the training and evaluation of increasingly sophisticated models.