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GoMAvatar: Efficient Animatable Human Modeling from Monocular Video Using Gaussians-on-Mesh
April 12, 2024, 4:46 a.m. | Jing Wen, Xiaoming Zhao, Zhongzheng Ren, Alexander G. Schwing, Shenlong Wang
cs.CV updates on arXiv.org arxiv.org
Abstract: We introduce GoMAvatar, a novel approach for real-time, memory-efficient, high-quality animatable human modeling. GoMAvatar takes as input a single monocular video to create a digital avatar capable of re-articulation in new poses and real-time rendering from novel viewpoints, while seamlessly integrating with rasterization-based graphics pipelines. Central to our method is the Gaussians-on-Mesh representation, a hybrid 3D model combining rendering quality and speed of Gaussian splatting with geometry modeling and compatibility of deformable meshes. We assess …
abstract arxiv avatar cs.cv digital digital avatar graphics human memory mesh modeling novel pipelines quality real-time rendering type video
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