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Deep Convolutional Generative Adversarial Networks (DCGANs) for Creating Pixel Art
By Lawrence Du
PROBLEM: Creating art for mobile apps takes skill and money.● Stickers are big business
○ LINE messenger - a chat app popular in Asia made over $250 million dollars from stickers in 2015
○ Facebook, Snapchat, and Twitter have augmented their apps with sticker marketplaces
● Artwork can easily meet or exceed the cost of programming for many games today
● In Asia, communicating with sticker art can be easier than writing text on mobile devices
Solution: Use Deep Learning for AI assisted art generation
Intelligent infill
Fake pictures of bedrooms
Solution: Use Deep Learning for AI assisted art generation
Intelligent infill
AI generated music album covers
An A.I. assistant for creating art
Implementation
DISCRIMINATOR
GENERATOR
Network Balancing
DISCRIMINATORLOSS
GENERATORLOSS
Using Pokémon as a training set
● Images of 722 Pokémon available ● 76,469 animation frames from the most recent generation (XY)● Feature engineering: 19231 frames from 231 Pokémon selected
for consistent naturalistic morphology.
Using Pokémon as a training set
● Images of 722 Pokémon available ● 76,469 animation frames from the most recent generation (XY)● Feature engineering: 19231 frames from 231 Pokémon selected
for consistent naturalistic morphology.
Implementation
● Wrote DCGAN using
● 30+ neural architecture combinations tested.● Expanded training set size by random application of
brightness, hue, contrast, and left-right transformations.● Training takes 20-30 minutes on Geforce GTX 1060 GPU● Python Flask
