NIDAR adds synthesized intensity to an existing point cloud using RGB appearance, a pseudo-NIR prior, intrinsic decomposition, and calibration. It requires RGB images + XYZ geometry + camera/LiDAR calibration. Existing nuScenes research example from the project page. The first portable demo targets Waymo-style exports; this figure is not a new release-validation run. Runtime destinations are relative to the chosen weights directory; files on the Hub are at the repository root. ARTIFACTS.json and SHA256SUMS provide sizes and checksums. Follow the source demo guide with source revision 8803e880e08662b07409f4bc9a9f6fb487101c99 or a compatible later revision. Python 3.10 and PyTorch 2.6 or…