May 14, 2024, 4:46 a.m. | Ancheng Lin, Jun Li

cs.CV updates on

arXiv:2405.06945v1 Announce Type: new
Abstract: Accurately reconstructing a 3D scene including explicit geometry information is both attractive and challenging. Geometry reconstruction can benefit from incorporating differentiable appearance models, such as Neural Radiance Fields and 3D Gaussian Splatting (3DGS). In this work, we propose a learnable scene model that incorporates 3DGS with an explicit geometry representation, namely a mesh. Our model learns the mesh and appearance in an end-to-end manner, where we bind 3D Gaussians to the mesh faces and perform …

abstract arxiv benefit differentiable fields geometry information mesh neural radiance fields type via work

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