Animatable Human

Animatable human modeling aims to create realistic, digitally rendered human avatars capable of dynamic pose changes and novel view generation from limited input data, such as monocular videos or a few images. Current research heavily utilizes implicit neural representations, including Gaussian splatting and neural radiance fields, often combined with techniques like linear blend skinning and graph neural networks to efficiently model complex body geometry and articulation. These advancements are driving progress in applications like virtual try-ons, animation, and virtual reality, offering more efficient and realistic human representation than traditional methods.