- VGGT: Visual Geometry Grounded Transformer - GitHub
Visual Geometry Grounded Transformer (VGGT, CVPR 2025) is a feed-forward neural network that directly infers all key 3D attributes of a scene, including extrinsic and intrinsic camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views, within seconds
- VGGT: Visual Geometry Grounded Transformer
We propose Visual Geometry Grounded Transformer (VGGT), a feed-forward neural network that directly predicts all key 3D scene attributes from single or multiple (up to hundreds) image views within seconds
- [2503. 11651] VGGT: Visual Geometry Grounded Transformer
We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views
- VGGT: Visual Geometry Grounded Transformer - CVF Open Access
We present VGGT, a feed-forward neural network that di-rectly infers all key 3D attributes of a scene, including cam-era parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views
- VGGT: Visual Geometry Grounded Transformer - IEEE Xplore
We present VGGT, a feed-forward neural network that directly infers all key 3D attributes of a scene, including camera parameters, point maps, depth maps, and 3
- facebook VGGT-1B · Hugging Face
Visual Geometry Grounded Transformer (VGGT, CVPR 2025) is a feed-forward neural network that directly infers all key 3D attributes of a scene, including extrinsic and intrinsic camera parameters, point maps, depth maps, and 3D point tracks, from one, a few, or hundreds of its views, within seconds
- VGGT is a Pure Neural Approach to 3D Vision - voxel51. com
VGGT is now available as a FiftyOne Zoo Model, making it accessible for immediate use in computer vision workflows The implementation provides a seamless way to generate depth maps, camera parameters, and 3D point clouds from images with just a few lines of code
- VGGT：重新定义3D视觉的统一基础模型 - CSDN博客
文章浏览阅读244次，点赞2次，收藏2次。VGGT：统一3D视觉的Transformer基础模型 Meta AI与牛津大学提出的VGGT创新性地统一了多种3D视觉任务，通过前馈式Transformer架构实现了高效的三维场景理解。该模型采用12亿参数的Transformer网络，设计交替注意力机制平衡局部特征与全局几何关系，仅需单次前向传播
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