3.4k citations · 6.8k across the 36 of their papers we have counts for
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cs.CV2016★ 4 cited
An Uncertain Future: Forecasting from Static Images using Variational Autoencoders
Jacob Walker, Carl Doersch, Abhinav Gupta +1
In a given scene, humans can often easily predict a set of immediate future events that might happen. However, generalized pixel-level anticipation in computer vision systems is di…
stat.ML2016★ 1.4k cited
Tutorial on Variational Autoencoders
Carl Doersch
In just three years, Variational Autoencoders (VAEs) have emerged as one of the most popular approaches to unsupervised learning of complicated distributions. VAEs are appealing be…