arXiv:1603.03875
Towards Building an RGBD-M Scanner
원문 초록
We present a portable device to capture both shape and reflectance of an indoor scene. Consisting of a Kinect, an IR camera and several IR LEDs, our device allows the user to acquire data in a similar way as he/she scans with a single Kinect. Scene geometry is reconstructed by KinectFusion. To estimate reflectance from incomplete and noisy observations, 3D vertices of the same material are identified by our material segmentation propagation algorithm. Then BRDF observations at these vertices are merged into a more complete and accurate BRDF for the material. Effectiveness of our device is demonstrated by quality results on real-world scenes.
함께 살펴볼 논문
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UnMix-NeRF: Spectral Unmixing Meets Neural Radiance Fields
MatSpectNet: Material Segmentation Network with Domain-Aware and Physically-Constrained Hyperspectral Reconstruction
DBAT: Dynamic Backward Attention Transformer for Material Segmentation with Cross-Resolution Patches
A Dense Material Segmentation Dataset for Indoor and Outdoor Scene Parsing
GaussianProperty: Integrating Physical Properties to 3D Gaussians with LMMs
Low-cost Robust Night-time Aerial Material Segmentation through Hyperspectral Data and Sparse Spatio-Temporal Learning
토론
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