cvg/nice-slam
NICE-SLAM is a neural implicit SLAM system for dense 3D reconstruction and camera tracking in large-scale indoor scenes.
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NICE-SLAM (Neural Implicit Scalable Encoding for SLAM) is a research system that reconstructs dense 3D geometry and tracks camera pose simultaneously using neural implicit representations learned via deep learning. It operates on RGB-D input to produce metric 3D maps without pre-trained models, with applications in robotics navigation and augmented reality.
Frequently asked
- What is cvg/nice-slam?
- NICE-SLAM is a neural implicit SLAM system for dense 3D reconstruction and camera tracking in large-scale indoor scenes.
- Is nice-slam open source?
- Yes — cvg/nice-slam is open source, released under the Apache-2.0 license.
- What language is nice-slam written in?
- cvg/nice-slam is primarily written in Python.
- How popular is nice-slam?
- cvg/nice-slam has 1.6k stars on GitHub.
- Where can I find nice-slam?
- cvg/nice-slam is on GitHub at https://github.com/cvg/nice-slam.