Emily L Denton

2017

Unsupervised Learning of Disentangled Representations from Video

NeurIPS 2017spotlight

We present a new model DRNET that learns disentangled image representations from video. Our approach leverages the temporal coherence of video and a novel adversarial loss to learn a representation that factorizes each frame into a stationary part and a temporally varying component. The disentangle…

Cited by 869 Source ↗PDF ↗code ↗Scholar ↗

2015

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks

Emily L Denton, Soumith Chintala, arthur szlam, Rob Fergus

NeurIPS 2015poster

In this paper we introduce a generative model capable of producing high quality samples of natural images. Our approach uses a cascade of convolutional networks (convnets) within a Laplacian pyramid framework to generate images in a coarse-to-fine fashion. At each level of the pyramid a separate gen…

Cited by 3162 Source ↗PDF ↗Scholar ↗

Unsupervised Learning of Disentangled Representations from Video

Deep Generative Image Models using a ￼Laplacian Pyramid of Adversarial Networks

Deep Generative Image Models using a Laplacian Pyramid of Adversarial Networks