ComboGAN: Unrestrained Scalability for Image Domain Translation

19 Dec 2017 Asha Anoosheh Eirikur Agustsson Radu Timofte Luc Van Gool

This year alone has seen unprecedented leaps in the area of learning-based image translation, namely CycleGAN, by Zhu et al. But experiments so far have been tailored to merely two domains at a time, and scaling them to more would require an quadratic number of models to be trained... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK SOURCE PAPER COMPARE
Facial Expression Translation CelebA ComboGAN AMT 9.6 # 5

Methods used in the Paper


METHOD TYPE
Batch Normalization
Normalization
Residual Connection
Skip Connections
PatchGAN
Discriminators
ReLU
Activation Functions
Tanh Activation
Activation Functions
Residual Block
Skip Connection Blocks
Instance Normalization
Normalization
Convolution
Convolutions
Leaky ReLU
Activation Functions
Sigmoid Activation
Activation Functions
GAN Least Squares Loss
Loss Functions
Cycle Consistency Loss
Loss Functions
CycleGAN
Generative Models