Human Generative

Human generative models aim to create realistic and controllable digital representations of humans, focusing on high-fidelity image and 3D model generation. Current research emphasizes advancements in diffusion models and GANs, often incorporating 3D parametric models like SMPL for improved pose and shape control, and leveraging multi-source data to enhance resolution and detail, particularly in challenging areas like faces and hands. This field is significant for its potential applications in animation, virtual try-ons, and virtual reality, while also driving methodological advancements in generative AI, particularly in handling complex, articulated structures.