27 citations · 108 across the 17 of their papers we have counts for
5 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,…
Towards Fairness in Visual Recognition: Effective Strategies for Bias Mitigation
Zeyu Wang, Klint Qinami, Ioannis Christos Karakozis +4
Computer vision models learn to perform a task by capturing relevant statistics from training data. It has been shown that models learn spurious age, gender, and race correlations…
CvxNet: Learnable Convex Decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani +3
Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a…
Text-based Editing of Talking-head Video
Ohad Fried, Ayush Tewari, Michael Zollhöfer +7
Editing talking-head video to change the speech content or to remove filler words is challenging. We propose a novel method to edit talking-head video based on its transcript to pr…
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…