1 citations · 1 across the 1 of their papers we have counts for
5 papers
Neural Jacobian Fields: Learning Intrinsic Mappings of Arbitrary Meshes
Noam Aigerman, Kunal Gupta, Vladimir G. Kim +3
This paper introduces a framework designed to accurately predict piecewise linear mappings of arbitrary meshes via a neural network, enabling training and evaluating over heterogen…
Contact-Aware Retargeting of Skinned Motion
Ruben Villegas, Duygu Ceylan, Aaron Hertzmann +2
This paper introduces a motion retargeting method that preserves self-contacts and prevents interpenetration. Self-contacts, such as when hands touch each other or the torso or the…
Stochastic Scene-Aware Motion Prediction
Mohamed Hassan, Duygu Ceylan, Ruben Villegas +4
A long-standing goal in computer vision is to capture, model, and realistically synthesize human behavior. Specifically, by learning from data, our goal is to enable virtual humans…
Neural Puppet: Generative Layered Cartoon Characters
Omid Poursaeed, Vladimir G. Kim, Eli Shechtman +2
We propose a learning based method for generating new animations of a cartoon character given a few example images. Our method is designed to learn from a traditionally animated se…
Minimally Supervised Learning of Affective Events Using Discourse Relations
Jun Saito, Yugo Murawaki, Sadao Kurohashi
Recognizing affective events that trigger positive or negative sentiment has a wide range of natural language processing applications but remains a challenging problem mainly becau…