most citedGoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo

1 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Sparse2DGS: Geometry-Prioritized Gaussian Splatting for Surface Reconstruction from Sparse Views

Jiang Wu, Rui Li, Yu Zhu +3

We present a Gaussian Splatting method for surface reconstruction using sparse input views. Previous methods relying on dense views struggle with extremely sparse Structure-from-Mo…

eess.IV2024

RoCoSDF: Row-Column Scanned Neural Signed Distance Fields for Freehand 3D Ultrasound Imaging Shape Reconstruction

Hongbo Chen, Yuchong Gao, Shuhang Zhang +3

The reconstruction of high-quality shape geometry is crucial for developing freehand 3D ultrasound imaging. However, the shape reconstruction of multi-view ultrasound data remains…

cs.CV2024

The Third Monocular Depth Estimation Challenge

Jaime Spencer, Fabio Tosi, Matteo Poggi +38

This paper discusses the results of the third edition of the Monocular Depth Estimation Challenge (MDEC). The challenge focuses on zero-shot generalization to the challenging SYNS-…

cs.CV2024★ 1 cited

GoMVS: Geometrically Consistent Cost Aggregation for Multi-View Stereo

Jiang Wu, Rui Li, Haofei Xu +4

Matching cost aggregation plays a fundamental role in learning-based multi-view stereo networks. However, directly aggregating adjacent costs can lead to suboptimal results due to…

cs.CV2024★ 1 cited

Boosting Multi-view Stereo with Late Cost Aggregation

Jiang Wu, Rui Li, Yu Zhu +3

Pairwise matching cost aggregation is a crucial step for modern learning-based Multi-view Stereo (MVS). Prior works adopt an early aggregation scheme, which adds up pairwise costs…