2 citations · 5 across the 3 of their papers we have counts for
3 papers
cs.CV2019★ 2 cited
A Performance Evaluation of Correspondence Grouping Methods for 3D Rigid Data Matching
Jiaqi Yang, Ke Xian, Peng Wang +1
Seeking consistent point-to-point correspondences between 3D rigid data (point clouds, meshes, or depth maps) is a fundamental problem in 3D computer vision. While a number of corr…
cs.CV2019★ 2 cited
Comparative evaluation of 2D feature correspondence selection algorithms
Chen Zhao, Jiaqi Yang, Yang Xiao +1
Correspondence selection aiming at seeking correct feature correspondences from raw feature matches is pivotal for a number of feature-matching-based tasks. Various 2D (image) corr…
cs.CV2019★ 1 cited
Learning to Fuse Local Geometric Features for 3D Rigid Data Matching
Jiaqi Yang, Chen Zhao, Ke Xian +2
This paper presents a simple yet very effective data-driven approach to fuse both low-level and high-level local geometric features for 3D rigid data matching. It is a common pract…