GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface
  Reconstruction
Reconstructing accurate surfaces with radiance fields has achieved remarkable
progress in recent years. However, prevailing approaches, primarily based on
Gaussian Splatting, are increasingly constrained by representational
bottlenecks. In this paper, we introduce GeoSVR, an explicit voxel-based
framework that explores and extends the under-investigated potential of sparse
voxels for achieving accurate, detailed, and complete surface reconstruction.
As strengths, sparse voxels support preserving the coverage completeness and
geometric clarity, while corresponding challenges also arise from absent scene
constraints and locality in surface refinement. To ensure correct scene
convergence, we first propose a Voxel-Uncertainty Depth Constraint that
maximizes the effect of monocular depth cues while presenting a voxel-oriented
uncertainty to avoid quality degradation, enabling effective and robust scene
constraints yet preserving highly accurate geometries. Subsequently, Sparse
Voxel Surface Regularization is designed to enhance geometric consistency for
tiny voxels and facilitate the voxel-based formation of sharp and accurate
surfaces. Extensive experiments demonstrate our superior performance compared
to existing methods across diverse challenging scenarios, excelling in
geometric accuracy, detail preservation, and reconstruction completeness while
maintaining high efficiency. Code is available at
https://github.com/Fictionarry/GeoSVR.
68d3e32c4402066be56e1a90
Jiahe Li
admin_assigned
2025-09-24T15:31:49.547Z
66eec3889cbe309858abb830
/avatars/aeaee6ee34c867d246b1c9334048351d.svg
Jiahe Li
user
Fictionary
68d3e32c4402066be56e1a91
Jiawei Zhang
68d3e32c4402066be56e1a92
Youmin Zhang
admin_assigned
2025-09-24T15:32:01.994Z
65e054827409351736166d73
/avatars/d56b8af16b47cdac7a47d7bc0563687a.svg
Youmin Zhang
user
Rock-youmi
68d3e32c4402066be56e1a93
Xiao Bai
68d3e32c4402066be56e1a94
Jin Zheng
68d3e32c4402066be56e1a95
Xiaohan Yu
admin_assigned
2025-09-24T15:32:16.933Z
68be6f5c0e70474611c18ce1
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/FPbaWvBxwvR7m6pABhTFo.png
Xiaohan Yu
user
XiaoHan630
68d3e32c4402066be56e1a96
Lin Gu
admin_assigned
2025-09-24T15:32:10.065Z
633fe5ced4fc96dd3a054db5
/avatars/f3f2810b97f5ef0e4f72d40278f00204.svg
Lin Gu
user
LinGu
GeoSVR: Taming Sparse Voxels for Geometrically Accurate Surface
  Reconstruction
Reconstructing accurate surfaces with radiance fields has achieved remarkable
progress in recent years. However, prevailing approaches, primarily based on
Gaussian Splatting, are increasingly constrained by representational
bottlenecks. In this paper, we introduce GeoSVR, an explicit voxel-based
framework that explores and extends the under-investigated potential of sparse
voxels for achieving accurate, detailed, and complete surface reconstruction.
As strengths, sparse voxels support preserving the coverage completeness and
geometric clarity, while corresponding challenges also arise from absent scene
constraints and locality in surface refinement. To ensure correct scene
convergence, we first propose a Voxel-Uncertainty Depth Constraint that
maximizes the effect of monocular depth cues while presenting a voxel-oriented
uncertainty to avoid quality degradation, enabling effective and robust scene
constraints yet preserving highly accurate geometries. Subsequently, Sparse
Voxel Surface Regularization is designed to enhance geometric consistency for
tiny voxels and facilitate the voxel-based formation of sharp and accurate
surfaces. Extensive experiments demonstrate our superior performance compared
to existing methods across diverse challenging scenarios, excelling in
geometric accuracy, detail preservation, and reconstruction completeness while
maintaining high efficiency. Code is available at
https://github.com/Fictionarry/GeoSVR.
GeoSVR, a voxel-based framework, improves surface reconstruction accuracy and detail using sparse voxels with depth constraints and surface regularization.
Gaussian Splatting GeoSVR voxel-based framework sparse voxels Voxel-Uncertainty Depth Constraint Sparse Voxel Surface Regularization geometric accuracy detail preservation reconstruction completeness