Open Peer Review. Open Publishing. Open Access. Open Discussion. Open Directory. Open Recommendations. Open API. Open Source.
Training Triplet Networks with GAN
Maciej Zieba, Lei Wang
Feb 17, 2017 (modified: Aug 23, 2017)ICLR 2017 workshop submissionreaders: everyone
Abstract:Triplet networks are widely used models that are characterized by good performance in classification and retrieval tasks. In this work we propose to train a triplet network by putting it as the discriminator in Generative Adversarial Nets (GANs). We make use of the good capability of representation learning of the discriminator to increase the predictive quality of the model. We evaluated our approach on Cifar10 and MNIST datasets and observed significant improvement on the classification performance using the simple k-nn method.
Enter your feedback below and we'll get back to you as soon as possible.