(NIPS 2016 Workshop) Semantic Segmentation using Adversarial Networks
Paper: https://arxiv.org/abs/1611.08408

Image-to-Image Translation Using Conditional Adversarial Networks
Paper: https://arxiv.org/pdf/1611.07004v1.pdf
Code: https://phillipi.github.io/pix2pix/

(NIPS 2016) Generating Images with Perceptual Similarity Metrics based on Deep Networks
Paper: http://lmb.informatik.uni-freiburg.de/Publications/2016/DB16c/inverting_GAN_nips2016_final.pdf
Supplement: http://lmb.informatik.uni-freiburg.de/Publications/2016/DB16c/inverting_GAN_nips2016_supp_final.pdf
Code: http://lmb.informatik.uni-freiburg.de/people/dosovits/code.html

(NIPS 2016) Synthesizing the preferred inputs for neurons in neural networks via deep generator networks
Paper: http://www.evolvingai.org/files/nguyen2016synthesizing.pdf
Code: https://github.com/Evolving-AI-Lab/synthesizing

(ICDM 2016) Learning Compatibility Across Categories for Heterogeneous Item Recommendation
Paper: https://cseweb.ucsd.edu/~jmcauley/pdfs/icdm16b.pdf

(ICCV 2015) Learning Visual Clothing Style with Heterogeneous Dyadic Co-occurrences
Paper: http://cseweb.ucsd.edu/~jmcauley/pdfs/iccv15.pdf
Supplement: https://goo.gl/OM1rAL
Code: https://vision.cornell.edu/se3/projects/clothing-style/

(SIGIR 2015) Image-based recommendations on styles and substitutes
Paper: https://cseweb.ucsd.edu/~jmcauley/pdfs/sigir15.pdf
Code: https://cseweb.ucsd.edu/~jmcauley/code/imageGraph.tar.gz

(NIPS 2016) Coupled Generative Adversarial Networks
Paper: https://arxiv.org/abs/1606.07536
Code: https://github.com/mingyuliutw/CoGAN

(ECCV 2016) Pixel-Level Domain Transfer
Paper: https://dgyoo.github.io/papers/eccv16.pdf
Supplement: https://dgyoo.github.io/papers/eccv16_supp.pdf
Code: https://github.com/fxia22/PixelDTGAN

(ICLR 2016) Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks
Paper: http://arxiv.org/abs/1511.06434
Code: https://github.com/Newmu/dcgan_code