Cited By
View all- Huang SJin XJiang QLiu L(2022)Deep learning for image colorization: Current and future prospectsEngineering Applications of Artificial Intelligence10.1016/j.engappai.2022.105006114(105006)Online publication date: Sep-2022
GAN-based image colorization techniques are capable of producing highly realistic color in real-time. Subjective assessment of these approaches has demonstrated that humans are unable to differentiate between a true RGB image and a colorized ...
Multimodal ambiguity and color bleeding remain challenging in colorization. To tackle these problems, we propose a new GAN-based colorization approach PalGAN, integrated with palette estimation and chromatic attention. To circumvent the ...
Images captured in low-light often suffer from severe quality degraded problems, such as low contrast and color distortion, which make it intractable for further computer vision tasks. To solve the problems above, we proposed a trainable parallel ...
Association for Computing Machinery
New York, NY, United States
Check if you have access through your login credentials or your institution to get full access on this article.
Sign inView or Download as a PDF file.
PDFView online with eReader.
eReaderView this article in HTML Format.
HTML Format