Wireframe Parsing With Guidance of Distance Map

IEEE Access

Shenghua Gao¹  Kun Huang² 

[1] School of Information Science and Technology, ShanghaiTech University, Shanghai, China;Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai, China;

关键词: Artificial neural networks;    computer vision;    feature extraction;    image edge detection;   

DOI  :  10.1109/ACCESS.2019.2943885

来源: DOAJ

【 摘 要 】

We propose an end-to-end method for simultaneously detecting local junctions and global wireframe in man-made environment. Our pipeline consists of an anchor-free junction detection module, a distance map learning module, and a line segment proposing and verification module. A set of line segments are proposed from the predicted junctions with guidance of the learned distance map, and further verified by the proposal verification module. Experimental results show that our method outperforms the previous state-of-the-art wireframe parser by a descent margin. In terms of line segments detection, our method shows competitive performance on standard benchmarks. The proposed networks are end-to-end trainable and efficient.^aaThe code will be released on github for reproduction of the results.

【 授权许可】

Unknown