A brief analysis of the holistically-nested edge detector

Este artículo está disponible en línea con materiales complementarios, software, conjuntos de datos y demostración en https://doi.org/10.5201/ipol.2022.422 This work describes the HED method for edge detection. HED uses a neural network based on a VGG16 backbone, supplemented with some extra layers for merging the results at different scales. The training was performed on an augmented version of the BSDS500 dataset. We perform a brief analysis of the results produced by HED, highlighting its quality but also indicating its limitations. Overall, HED produces state-of-the-art results.