most citedAn Error-Matching Exclusion Method for Accelerating Visual SLAM

2 citations · 3 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

9 papers · 1 filter

cs.CV2025

Glass Surface Detection: Leveraging Reflection Dynamics in Flash/No-flash Imagery

Tao Yan, Zeyu Wang, Hao Huang +6

Glass surfaces are ubiquitous in daily life, typically appearing colorless, transparent, and lacking distinctive features. These characteristics make glass surface detection a chal…

cs.CV2025

GACO-CAD: Geometry-Augmented and Conciseness-Optimized CAD Model Generation from Single Image

Yinghui Wang, Xinyu Zhang, Peng Du

Generating editable, parametric CAD models from a single image holds great potential to lower the barriers of industrial concept design. However, current multi-modal large language…

cs.CV2025

Occlusion-Aware Self-Supervised Monocular Depth Estimation for Weak-Texture Endoscopic Images

Zebo Huang, Yinghui Wang

We propose a self-supervised monocular depth estimation network tailored for endoscopic scenes, aiming to infer depth within the gastrointestinal tract from monocular images. Exist…

cs.CV2024★ 2 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.CV2024★ 1 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…