Visual‐attention GAN for interior sketch colourisation. Issue 4 (5th January 2021)
- Record Type:
- Journal Article
- Title:
- Visual‐attention GAN for interior sketch colourisation. Issue 4 (5th January 2021)
- Main Title:
- Visual‐attention GAN for interior sketch colourisation
- Authors:
- Li, Xinrong
Li, Hong
Wang, Chiyu
Hu, Xun
Zhang, Wei - Abstract:
- Abstract: In the professional field of interior designing, sketch colouring is often a time‐consuming and vapidity task. The traditional neural network does not handle the semantic relationship of sketch lines well, and the colouring effect is unsatisfactory. This paper proposes visual‐attention generative adversarial network (VAGAN), which enhances the processing effect of edge semantics, strengthens the network to line edge recognition ability, as well as reduces colour overflow and improved model colouring result. In addition, a two‐stage training mode is used to simplify the training of rare samples. The simple line draft input into the trained VAGAN, output natural, realistic colour pictures. The experimental results show that, compared with the existing methods, the proposed method can better deal with the problem of sketch and generate stable and reliable images.
- Is Part Of:
- IET image processing. Volume 15:Issue 4(2021)
- Journal:
- IET image processing
- Issue:
- Volume 15:Issue 4(2021)
- Issue Display:
- Volume 15, Issue 4 (2021)
- Year:
- 2021
- Volume:
- 15
- Issue:
- 4
- Issue Sort Value:
- 2021-0015-0004-0000
- Page Start:
- 997
- Page End:
- 1007
- Publication Date:
- 2021-01-05
- Subjects:
- Image recognition -- Computer vision and image processing techniques -- Graphics techniques -- Neural nets
Image processing -- Periodicals
621.36705 - Journal URLs:
- http://digital-library.theiet.org/content/journals/iet-ipr ↗
http://ieeexplore.ieee.org/servlet/opac?punumber=4149689 ↗
http://www.ietdl.org/IET-IPR ↗
https://ietresearch.onlinelibrary.wiley.com/journal/17519667 ↗
http://www.theiet.org/ ↗ - DOI:
- 10.1049/ipr2.12080 ↗
- Languages:
- English
- ISSNs:
- 1751-9659
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4363.252600
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 26192.xml