Pixel-Wise Symbol Spotting via Progressive Points Location for Parsing
  CAD Images
Junbiao Pang Zailin Dong Jiaxin Deng Mengyuan Zhu Yunwei Zhang
Parsing Computer-Aided Design (CAD) drawings is a fundamental step for CAD
revision, semantic-based management, and the generation of 3D prototypes in
both the architecture and engineering industries. Labeling symbols from a CAD
drawing is a challenging yet notorious task from a practical point of view. In
this work, we propose to label and spot symbols from CAD images that are
converted from CAD drawings. The advantage of spotting symbols from CAD images
lies in the low requirement of labelers and the low-cost annotation. However,
pixel-wise spotting symbols from CAD images is challenging work. We propose a
pixel-wise point location via Progressive Gaussian Kernels (PGK) to balance
between training efficiency and location accuracy. Besides, we introduce a
local offset to the heatmap-based point location method. Based on the keypoints
detection, we propose a symbol grouping method to redraw the rectangle symbols
in CAD images. We have released a dataset containing CAD images of equipment
rooms from telecommunication industrial CAD drawings. Extensive experiments on
this real-world dataset show that the proposed method has good generalization
ability.