arXiv:2208.04307
공식 코드 · Papers with Code
PlaneFormers: From Sparse View Planes to 3D Reconstruction
원문 초록
We present an approach for the planar surface reconstruction of a scene from images with limited overlap. This reconstruction task is challenging since it requires jointly reasoning about single image 3D reconstruction, correspondence between images, and the relative camera pose between images. Past work has proposed optimization-based approaches. We introduce a simpler approach, the PlaneFormer, that uses a transformer applied to 3D-aware plane tokens to perform 3D reasoning. Our experiments show that our approach is substantially more effective than prior work, and that several 3D-specific design decisions are crucial for its success.
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HRGS: Hierarchical Gaussian Splatting for Memory-Efficient High-Resolution 3D Reconstruction
Sparse2DGS: Sparse-View Surface Reconstruction using 2D Gaussian Splatting with Dense Point Cloud
From Low Field to High Value: Robust Cortical Mapping from Low-Field MRI
Geometric Prior-Guided Neural Implicit Surface Reconstruction in the Wild
3D Surface Reconstruction with Enhanced High-Frequency Details
TSGS: Improving Gaussian Splatting for Transparent Surface Reconstruction via Normal and De-lighting Priors
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