File Exchange

image thumbnail


version 1.0.1 (205 MB) by Yui Chun Leung
MATLAB implementations of Generative Adversarial Networks -- from GAN to Pixel2Pixel, CycleGAN


Updated 19 Mar 2021

From GitHub

View Version History

View license on GitHub

Collection of MATLAB implementations of Generative Adversarial Networks (GANs) suggested in research papers. It includes GAN, conditional-GAN, info-GAN, Adversarial AutoEncoder, Pix2Pix, CycleGAN and more, and the models are applied to different datasets such as MNIST, celebA and Facade.

Cite As

Yui Chun Leung (2021). Matlab-GAN (, GitHub. Retrieved .

Y. LeCun and C. Cortes, “MNIST handwritten digitdatabase,” 2010. [MNIST]

J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, andL. Fei-Fei, “ImageNet: A Large-Scale Hierarchical Image Database,” inCVPR09, 2009. [Apple2Orange (ImageNet)]

R. Tyleček and R. Šára, “Spatial pattern templates forrecognition of objects with regular structure,” inProc.GCPR, (Saarbrucken, Germany), 2013. [Facade]

Z. Liu, P. Luo, X. Wang, and X. Tang, “Deep learn-ing face attributes in the wild,” inProceedings of In-ternational Conference on Computer Vision (ICCV),December 2015. [CelebA]

Goodfellow, Ian J. et al. “Generative Adversarial Networks.” ArXiv abs/1406.2661 (2014): n. pag. (GAN)

Radford, Alec et al. “Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks.” CoRR abs/1511.06434 (2015): n. pag. (DCGAN)

Denton, Emily L. et al. “Semi-Supervised Learning with Context-Conditional Generative Adversarial Networks.” ArXiv abs/1611.06430 (2017): n. pag. (CGAN)

Odena, Augustus et al. “Conditional Image Synthesis with Auxiliary Classifier GANs.” ICML (2016). (ACGAN)

Chen, Xi et al. “InfoGAN: Interpretable Representation Learning by Information Maximizing Generative Adversarial Nets.” NIPS (2016). (InfoGAN)

Makhzani, Alireza et al. “Adversarial Autoencoders.” ArXiv abs/1511.05644 (2015): n. pag. (AAE)

Isola, Phillip et al. “Image-to-Image Translation with Conditional Adversarial Networks.” 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2016): 5967-5976. (Pix2Pix)

J.-Y. Zhu, T. Park, P. Isola, and A. A. Efros, “Unpairedimage-to-image translation using cycle-consistent ad-versarial networks,” 2017. (CycleGAN)

Comments and Ratings (11)

伟 代

zhengjian wu

Carlos Ponce

seong-seop yun

Liu Fred

Takuji Fukumoto


Reham Barah

Chih-En Kuo


great work! thank you for sharing your files!

MATLAB Release Compatibility
Created with R2019b
Compatible with R2019b to R2020a
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!