articleJun 10, 2025Closed access

VGGT: Visual Geometry Grounded Transformer

University of Oxford

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Abstract

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. This approach is a step forward in 3D computer vision, where models have typically been constrained to and specialized for single tasks. It is also simple and efficient, reconstructing images in under one second, and still outperforming alternatives that require post-processing with visual geometry optimization techniques. The network achieves state-of-the-art results in multiple 3D tasks, including camera parameter estimation, multi-view depth estimation, dense point cloud reconstruction, and…

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Authors

6

Topics & keywords

Keywords
  • Transformer
  • Computer science
  • Geometry
  • Mathematics
  • Electrical engineering
  • Engineering
  • Voltage
UN Sustainable Development Goals
  • Affordable and clean energy
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