Textured 3D Shape

Research on textured 3D shape generation focuses on creating realistic, high-resolution 3D models with surface textures from various input sources, including text descriptions, single example shapes, or 2D images. Current approaches leverage deep learning models, such as diffusion models and GANs, often employing neural implicit representations (like unsigned distance fields) or voxel-based methods, and incorporating techniques like differentiable rendering and optimal wavelet transformations to improve efficiency and quality. This field is significant for its potential to revolutionize 3D modeling pipelines, enabling faster and more accessible creation of realistic virtual objects for applications ranging from computer graphics and gaming to virtual and augmented reality.