most citedAn Error-Matching Exclusion Method for Accelerating Visual SLAM

2 citations · 3 across the 5 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2025

Reprojection-Guided 3D Gaussian Splatting Diffusion for Weakly Supervised Single-Image Normal Estimation

Yanxing Liang, Yinghui Wang, Wei Li +2

We propose CLONE, a Continuous Latent Optimization framework for Normal Estimation via 3D Gaussian splatting. The core idea is to construct an image-geometry-image consistency stra…

cs.CV2025

Feature Point Extraction for Extra-Affine Image

Tao Wang, Yinghui Wang, Yanxing Liang +4

The issue concerning the significant decline in the stability of feature extraction for images subjected to large-angle affine transformations, where the angle exceeds 50 degrees,…

cs.CV20242 cited

An Error-Matching Exclusion Method for Accelerating Visual SLAM

Shaojie Zhang, Yinghui Wang, Jiaxing Ma +7

In Visual SLAM, achieving accurate feature matching consumes a significant amount of time, severely impacting the real-time performance of the system. This paper proposes an accele…

cs.CV20241 cited

A Feature Matching Method Based on Multi-Level Refinement Strategy

Shaojie Zhang, Yinghui Wang, Jiaxing Ma +7

Feature matching is a fundamental and crucial process in visual SLAM, and precision has always been a challenging issue in feature matching. In this paper, based on a multi-level f…

cs.CV2024

A Robust Error-Resistant View Selection Method for 3D Reconstruction

Shaojie Zhang, Yinghui Wang, Bin Nan +7

To address the issue of increased triangulation uncertainty caused by selecting views with small camera baselines in Structure from Motion (SFM) view selection, this paper proposes…

cs.CV2024

Region Feature Descriptor Adapted to High Affine Transformations

Shaojie Zhang, Yinghui Wang, Bin Nan +7

To address the issue of feature descriptors being ineffective in representing grayscale feature information when images undergo high affine transformations, leading to a rapid decl…