41 citations · 122 across the 14 of their papers we have counts for
4 papers · 1 filter
Local Deep Implicit Functions for 3D Shape
Kyle Genova, Forrester Cole, Avneesh Sud +2
The goal of this project is to learn a 3D shape representation that enables accurate surface reconstruction, compact storage, efficient computation, consistency for similar shapes,…
Unsupervised Learning of Object Structure and Dynamics from Videos
Matthias Minderer, Chen Sun, Ruben Villegas +3
Extracting and predicting object structure and dynamics from videos without supervision is a major challenge in machine learning. To address this challenge, we adopt a keypoint-bas…
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…
Learning Shape Templates with Structured Implicit Functions
Kyle Genova, Forrester Cole, Daniel Vlasic +3
Template 3D shapes are useful for many tasks in graphics and vision, including fitting observation data, analyzing shape collections, and transferring shape attributes. Because of…