[IPOL announce] new article: A Brief Analysis of the Dense Extreme Inception Network for Edge Detection

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2022/423/

Rafael Grompone von Gioi, and Gregory Randall,

A Brief Analysis of the Dense Extreme Inception Network for Edge Detection,
Image Processing On Line, 12 (2022), pp. 389–403.
https://doi.org/10.5201/ipol.2022.423

Abstract
This work describes DexiNed, a Dense Extreme Inception Network for Edge 
Detection proposed by Xavier Soria, Edgar Riba and Angel Sappa in [IEEE 
Winter Conference on Applications of Computer Vision (WACV), 2020]. The 
network is organized in blocks that extract edges at different 
resolutions, which are then merged to produce a multiscale edge map. For 
training, the authors introduced an annotated dataset (BIPED) 
specifically designed for edge detection. We perform a brief analysis of 
the results produced by DexiNed, highlighting its quality but also 
indicating its limitations. Overall, DexiNed produces state-of-the-art 
results.