astra-vision/SceneRF

[ICCV 2023] Official implementation of "SceneRF: Self-Supervised Monocular 3D Scene Reconstruction with Radiance Fields"

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Emerging

This project helps perception engineers or robotics developers reconstruct detailed 3D scenes from a single video camera feed. You input monocular video sequences of environments like streets or indoor spaces, and it outputs a rich 3D representation, including depth maps and novel views. This is useful for anyone building autonomous systems that need to understand and interact with their physical surroundings.

379 stars. No commits in the last 6 months.

Use this if you need to generate dense 3D models and synthesize new views of a scene using only standard video camera input, without requiring specialized depth sensors.

Not ideal if you require real-time 3D reconstruction on low-power edge devices or if high-precision metric accuracy across extremely large, unbounded environments is your primary concern.

3D-reconstruction robotics-perception autonomous-vehicles computer-vision scene-understanding
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 15 / 25

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Stars

379

Forks

33

Language

Python

License

Apache-2.0

Last pushed

Mar 03, 2024

Commits (30d)

0

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