136 citations · 305 across the 24 of their papers we have counts for
6 papers · 1 filter
Dimensions of Motion: Monocular Prediction through Flow Subspaces
Richard Strong Bowen, Richard Tucker, Ramin Zabih +1
We introduce a way to learn to estimate a scene representation from a single image by predicting a low-dimensional subspace of optical flow for each training example, which encompa…
SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting
Varun Jampani, Huiwen Chang, Kyle Sargent +8
Single image 3D photography enables viewers to view a still image from novel viewpoints. Recent approaches combine monocular depth networks with inpainting networks to achieve comp…
Consistent Depth of Moving Objects in Video
Zhoutong Zhang, Forrester Cole, Richard Tucker +2
We present a method to estimate depth of a dynamic scene, containing arbitrary moving objects, from an ordinary video captured with a moving camera. We seek a geometrically and tem…
KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control
Tomas Jakab, Richard Tucker, Ameesh Makadia +3
We introduce KeypointDeformer, a novel unsupervised method for shape control through automatically discovered 3D keypoints. We cast this as the problem of aligning a source 3D obje…
De-rendering the World's Revolutionary Artefacts
Shangzhe Wu, Ameesh Makadia, Jiajun Wu +3
Recent works have shown exciting results in unsupervised image de-rendering -- learning to decompose 3D shape, appearance, and lighting from single-image collections without explic…
Repopulating Street Scenes
Yifan Wang, Andrew Liu, Richard Tucker +4
We present a framework for automatically reconfiguring images of street scenes by populating, depopulating, or repopulating them with objects such as pedestrians or vehicles. Appli…