17 citations · 33 across the 4 of their papers we have counts for
6 papers
PIM: Video Coding using Perceptual Importance Maps
Evgenya Pergament, Pulkit Tandon, Oren Rippel +6
Human perception is at the core of lossy video compression, with numerous approaches developed for perceptual quality assessment and improvement over the past two decades. In the d…
An Interactive Annotation Tool for Perceptual Video Compression
Evgenya Pergament, Pulkit Tandon, Kedar Tatwawadi +6
Human perception is at the core of lossy video compression and yet, it is challenging to collect data that is sufficiently dense to drive compression. In perceptual quality assessm…
ELF-VC: Efficient Learned Flexible-Rate Video Coding
Oren Rippel, Alexander G. Anderson, Kedar Tatwawadi +3
While learned video codecs have demonstrated great promise, they have yet to achieve sufficient efficiency for practical deployment. In this work, we propose several novel ideas fo…
Learned Video Compression
Oren Rippel, Sanjay Nair, Carissa Lew +3
We present a new algorithm for video coding, learned end-to-end for the low-latency mode. In this setting, our approach outperforms all existing video codecs across nearly the enti…
The High-Dimensional Geometry of Binary Neural Networks
Alexander G. Anderson, Cory P. Berg
Recent research has shown that one can train a neural network with binary weights and activations at train time by augmenting the weights with a high-precision continuous latent va…
DeepMovie: Using Optical Flow and Deep Neural Networks to Stylize Movies
Alexander G. Anderson, Cory P. Berg, Daniel P. Mossing +1
A recent paper by Gatys et al. describes a method for rendering an image in the style of another image. First, they use convolutional neural network features to build a statistical…