https://github.com/bchao1/dcgan-random-anime-generation
Anime generation using vanilla GAN, WGAN, and LSGAN.
Science Score: 13.0%
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
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○Academic publication links
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (2.8%) to scientific vocabulary
Keywords
anime
gan
lsgan
Last synced: 9 months ago
·
JSON representation
Repository
Anime generation using vanilla GAN, WGAN, and LSGAN.
Basic Info
Statistics
- Stars: 0
- Watchers: 1
- Forks: 1
- Open Issues: 0
- Releases: 0
Topics
anime
gan
lsgan
Created over 7 years ago
· Last pushed over 7 years ago
Metadata Files
Readme
README.md
DCGAN Anime Generation
- Tried out vanilla GAN and LSGAN for anime generation using DCGAN structure.
- Collected our own dataset (scraped images from a online manga store)
Training process
- Used original DCGAN paper settings.
- Halved the discriminator loss to balance G/D gradient descent schedule.
- Used soft-labeling (0.8/0.9 ~ 1)
Results
||Given dataset|Our own dataset|
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|Real Distribution|
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|GAN|
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|LSGAN|
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|WGAN||
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Problems
- Our own dataset has some outliers (darker skin tone).
Owner
- Name: Brian Chao
- Login: bchao1
- Kind: user
- Location: Stanford, California
- Company: Stanford University
- Website: https://bchao1.github.io
- Twitter: BrianCChao
- Repositories: 14
- Profile: https://github.com/bchao1
Stanford Ph.D. student. Research in computational photography, displays, and computer graphics. Open source enthusiast.
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