isarandi/nlf
A deep learning method published at NeurIPS 2024 that estimates 3D human pose and body shape from images or video using neural networks.
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Neural Localizer Fields (NLF) provides models for continuous 3D human pose and shape estimation, enabling reconstruction of human body geometry from visual data. The project includes PyTorch and TensorFlow implementations with training code and pre-trained models for non-commercial research use, demonstrated in a demo notebook.
Frequently asked
- What is isarandi/nlf?
- A deep learning method published at NeurIPS 2024 that estimates 3D human pose and body shape from images or video using neural networks.
- Is nlf open source?
- Yes — isarandi/nlf is open source, released under the MIT license.
- What language is nlf written in?
- isarandi/nlf is primarily written in Python.
- How popular is nlf?
- isarandi/nlf has 445 stars on GitHub.
- Where can I find nlf?
- isarandi/nlf is on GitHub at https://github.com/isarandi/nlf.