正在加载视频...

视频加载失败

Source code released: 3DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splatting

18,357 次观看 • 2 年前 •via X (Twitter)

2 条评论

softyoda 的头像
softyoda2 年前

Is there a just middle between monocular video input and array of 64 1000€ cameras ? (like I got 3 GoPro + 1DSLR + 1 Smartphone, could be nice to have ways to almost sync and register all)

MrNeRF 的头像
MrNeRF2 年前

No experience with that. Why don't you try it and make a project out of it?

相关视频

Nvidia announces GAvatar: Animatable 3D Gaussian Avatars with Implicit Mesh Learning paper page: Gaussian splatting has emerged as a powerful 3D representation that harnesses the advantages of both explicit (mesh) and implicit (NeRF) 3D representations. In this paper, we seek to leverage Gaussian splatting to generate realistic animatable avatars from textual descriptions, addressing the limitations (e.g., flexibility and efficiency) imposed by mesh or NeRF-based representations. However, a naive application of Gaussian splatting cannot generate high-quality animatable avatars and suffers from learning instability; it also cannot capture fine avatar geometries and often leads to degenerate body parts. To tackle these problems, we first propose a primitive-based 3D Gaussian representation where Gaussians are defined inside pose-driven primitives to facilitate animation. Second, to stabilize and amortize the learning of millions of Gaussians, we propose to use neural implicit fields to predict the Gaussian attributes (e.g., colors). Finally, to capture fine avatar geometries and extract detailed meshes, we propose a novel SDF-based implicit mesh learning approach for 3D Gaussians that regularizes the underlying geometries and extracts highly detailed textured meshes. Our proposed method, GAvatar, enables the large-scale generation of diverse animatable avatars using only text prompts. GAvatar significantly surpasses existing methods in terms of both appearance and geometry quality, and achieves extremely fast rendering (100 fps) at 1K resolution.

AK

141,058 次观看 • 2 年前