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Honghua Li

4 accepted papers

2022

GAT-CADNet: Graph Attention Network for Panoptic Symbol Spotting in CAD Drawings

CVPR 2022poster

Spotting graphical symbols from the computer-aided design (CAD) drawings is essential to many industrial applications. Different from raster images, CAD drawings are vector graphics consisting of geometric primitives such as segments, arcs, and circles. By treating each CAD drawing as a graph, we pr…

Cited by 18PDFScholar
2021

FloorPlanCAD: A Large-Scale CAD Drawing Dataset for Panoptic Symbol Spotting

ICCV 2021poster

Access to large and diverse computer-aided design (CAD) drawings is critical for developing symbol spotting algorithms. In this paper, we present FloorPlanCAD, a large-scale real-world CAD drawing dataset containing over 10,000 floor plans, ranging from residential to commercial buildings. CAD drawi…

Cited by 50PDFcodeScholar
2021

Single-Shot is Enough: Panoramic Infrastructure Based Calibration of Multiple Cameras and 3D LiDARs

IROS 2021poster

The integration of multiple cameras and 3D Li-DARs has become basic configuration of augmented reality devices, robotics, and autonomous vehicles. The calibration of multi-modal sensors is crucial for a system to properly function, but it remains tedious and impractical for mass production. Moreover…

Cited by 27SourceScholar
2019

SANet: Scene Agnostic Network for Camera Localization

ICCV 2019poster

This paper presents a scene agnostic neural architecture for camera localization, where model parameters and scenes are independent from each other.Despite recent advancement in learning based methods, most approaches require training for each scene one by one, not applicable for online applications…

Cited by 99PDFScholar