On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs-Reference-Cited by-同舟云学术

On Using Perceptual Loss within the U-Net Architecture for the Semantic Inpainting of Textile Artefacts with Traditional Motifs

Published:2022-09 Issue: Volume: Page:
ISSN:
Container-title:2022 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)
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Author:

Stoean Catalin¹,Bacanin Nebojsa²,Stoean Ruxandra¹,Ionescu Leonard³,Alecsa Cristian³,Hotoleanu Mircea³,Atencia Miguel⁴,Joya Gonzalo⁴

Affiliation:

1. University of Craiova,Faculty of Sciences,Department of Computer Science,Romania

2. Singidunum University,Faculty of Informatics and Computing,Belgrade,Serbia

3. Romanian Institute of Science and Technology,Artificial Intelligence and Machine Learning Team,Cluj-Napoca,Romania

4. Universidad de Málaga,Spain

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10130844/10130822/10131036.pdf?arnumber=10131036

Reference16 articles.

1. Deep Learning-Based Masonry Wall Image Analysis

2. Towards an Inpainting Framework for Visual Cultural Heritage

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4. U-net: Convolutional networks for biomedical image segmentation;ronneberger;International Conference on Medical Image Computing and Computer-Assisted Intervention,2015

5. Pepsi++: Fast and lightweight network for image inpainting;shin;IEEE Transactions on Neural Networks and Learning Systems,2020

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