Personalized 3D

Personalized 3D modeling focuses on creating realistic, individual-specific 3D representations from limited input data, such as a single image or a small set of images. Current research emphasizes developing efficient algorithms, often leveraging generative adversarial networks (GANs) and diffusion models, to generate high-quality 3D models that accurately capture individual features while maintaining temporal consistency in video applications. This work is driven by the need for improved realism in virtual try-ons, telepresence systems, and other applications requiring accurate and personalized 3D human representations, impacting fields ranging from computer graphics to e-commerce.