Be a cartoonist : editing anime images using generative adversarial network
With the rise in popularity of generative models, many studies have started to look at furthering its applicability as well as its performance. One such application is in image-to-image translation which can be used to transform an image from domain A to domain B. However, in a scenario where the...
Saved in:
Main Author: | Koh, Tong Liang |
---|---|
Other Authors: | Liu Ziwei |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2022
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/156440 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Augmenting image data using generative adversarial networks (GAN)
by: Liu, Xinchi
Published: (2024) -
Multi-stage generative adversarial networks for generating pavement crack images
by: Han, Chengjia, et al.
Published: (2024) -
Anime characters creation using generative adversarial networks with user inputs
by: Ang, Himari Lixin
Published: (2024) -
Haze removal from an image or a video via generative adversarial networks
by: Chen, Zhong Jiang
Published: (2024) -
High-quality face image generated with conditional boundary equilibrium generative adversarial networks
by: Huang, Bin, et al.
Published: (2020)