most citedComparative evaluation of 2D feature correspondence selection algorithms

2 citations · 2 across the 4 of their papers we have counts for

collaborators

6 papers

cs.CV2020

On Efficient and Robust Metrics for RANSAC Hypotheses and 3D Rigid Registration

Jiaqi Yang, Zhiqiang Huang, Siwen Quan +3

This paper focuses on developing efficient and robust evaluation metrics for RANSAC hypotheses to achieve accurate 3D rigid registration. Estimating six-degree-of-freedom (6-DoF) p…

cs.CV2020

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…

cs.CV2020

ECML: An Ensemble Cascade Metric Learning Mechanism towards Face Verification

Fu Xiong, Yang Xiao, Zhiguo Cao +3

Face verification can be regarded as a 2-class fine-grained visual recognition problem. Enhancing the feature's discriminative power is one of the key problems to improve its perfo…

cs.CV2020

From Open Set to Closed Set: Supervised Spatial Divide-and-Conquer for Object Counting

Haipeng Xiong, Hao Lu, Chengxin Liu +3

Visual counting, a task that aims to estimate the number of objects from an image/video, is an open-set problem by nature, i.e., the number of population can vary in [0, inf) in th…

cs.CV2019

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…

cs.CV20192 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…