2 citations · 5 across the 4 of their papers we have counts for
8 papers · 1 filter
3D Correspondence Grouping with Compatibility Features
Jiaqi Yang, Jiahao Chen, Zhiqiang Huang +3
We present a simple yet effective method for 3D correspondence grouping. The objective is to accurately classify initial correspondences obtained by matching local geometric descri…
LRF-Net: Learning Local Reference Frames for 3D Local Shape Description and Matching
Angfan Zhu, Jiaqi Yang, Weiyue Zhao +1
The local reference frame (LRF) acts as a critical role in 3D local shape description and matching. However, most of existing LRFs are hand-crafted and suffer from limited repeatab…
Iterative Clustering with Game-Theoretic Matching for Robust Multi-consistency Correspondence
Chen Zhao, Jiaqi Yang, Ke Xian +2
Matching corresponding features between two images is a fundamental task to computer vision with numerous applications in object recognition, robotics, and 3D reconstruction. Curre…
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…
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…
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…