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A human 3D avatar is one of the important elements in the metaverse, and themodeling effect directly affects people's visual experience. However, the humanbody has a complex topology and diverse details, so it is often expensive,time-consuming, and laborious to build a satisfactory model. Recent studieshave proposed a novel method, implicit neural representation, which is acontinuous representation method and can describe objects with arbitrarytopology at arbitrary resolution. Researchers have applied implicit neuralrepresentation to human 3D avatar modeling and obtained more excellent resultsthan traditional methods. This paper comprehensively reviews the application ofimplicit neural representation in human body modeling. First, we introducethree implicit representations of occupancy field, SDF, and NeRF, and make aclassification of the literature investigated in this paper. Then theapplication of implicit modeling methods in the body, hand, and head arecompared and analyzed respectively. Finally, we point out the shortcomings ofcurrent work and provide available suggestions for researchers.

Human 3D Avatar Modeling with Implicit Neural Representation: A Brief Survey