7 citations · 9 across the 4 of their papers we have counts for
4 papers
LeCO-NeRF: Learning Continuous and Compact Large-Scale Occupancy for Urban Scenes
Zhenxing Mi, Dan Xu
In NeRF, a critical problem is to effectively estimate the occupancy to guide empty-space skipping and point sampling. Grid-based methods work well for small-scale scenes. However,…
Generalized Binary Search Network for Highly-Efficient Multi-View Stereo
Zhenxing Mi, Di Chang, Dan Xu
Multi-view Stereo (MVS) with known camera parameters is essentially a 1D search problem within a valid depth range. Recent deep learning-based MVS methods typically densely sample…
DeepDT: Learning Geometry From Delaunay Triangulation for Surface Reconstruction
Yiming Luo, Zhenxing Mi, Wenbing Tao
In this paper, a novel learning-based network, named DeepDT, is proposed to reconstruct the surface from Delaunay triangulation of point cloud. DeepDT learns to predict inside/outs…
SSRNet: Scalable 3D Surface Reconstruction Network
Zhenxing Mi, Yiming Luo, Wenbing Tao
Existing learning-based surface reconstruction methods from point clouds are still facing challenges in terms of scalability and preservation of details on large-scale point clouds…