activity
20152019
most citedDeepStereo: Learning to Predict New Views from the World's Imagery

86 citations · 160 across the 5 of their papers we have counts for

collaborators

7 papers

cs.CV201921 cited

DeepView: View Synthesis with Learned Gradient Descent

John Flynn, Michael Broxton, Paul Debevec +5

We present a novel approach to view synthesis using multiplane images (MPIs). Building on recent advances in learned gradient descent, our algorithm generates an MPI from a set of…

cs.CV201910 cited

Pushing the Boundaries of View Extrapolation with Multiplane Images

Pratul P. Srinivasan, Richard Tucker, Jonathan T. Barron +3

We explore the problem of view synthesis from a narrow baseline pair of images, and focus on generating high-quality view extrapolations with plausible disocclusions. Our method bu…

cs.CV20192 cited

Learning the Depths of Moving People by Watching Frozen People

Zhengqi Li, Tali Dekel, Forrester Cole +4

We present a method for predicting dense depth in scenarios where both a monocular camera and people in the scene are freely moving. Existing methods for recovering depth for dynam…

cs.CV201741 cited

StreetStyle: Exploring world-wide clothing styles from millions of photos

Kevin Matzen, Kavita Bala, Noah Snavely

Each day billions of photographs are uploaded to photo-sharing services and social media platforms. These images are packed with information about how people live around the world.…

cs.CV2017

Shading Annotations in the Wild

Balazs Kovacs, Sean Bell, Noah Snavely +1

Understanding shading effects in images is critical for a variety of vision and graphics problems, including intrinsic image decomposition, shadow removal, image relighting, and in…

cs.CV2016

From A to Z: Supervised Transfer of Style and Content Using Deep Neural Network Generators

Paul Upchurch, Noah Snavely, Kavita Bala

We propose a new neural network architecture for solving single-image analogies - the generation of an entire set of stylistically similar images from just a single input image. So…