Daniel Holden

According to our database, Daniel Holden authored at least 20 papers between 2015 and 2023.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2023

ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech.

Saeed Ghorbani, Ylva Ferstl, Daniel Holden, Nikolaus F. Troje, Marc-André Carbonneau

Comput. Graph. Forum, February, 2023

2021

SuperTrack: motion tracking for physically simulated characters using supervised learning.

Levi Fussell, Kevin Bergamin, Daniel Holden

ACM Trans. Graph., 2021

Artist guided generation of video game production quality face textures.

Christian Murphy, Sudhir P. Mudur, Daniel Holden, Marc-André Carbonneau, Donya Ghafourzadeh, Andre Beauchamp

Comput. Graph., 2021

2020

Learned motion matching.

Daniel Holden, Oussama Kanoun, Maksym Perepichka, Tiberiu Popa

ACM Trans. Graph., 2020

Appearance Controlled Face Texture Generation for Video Game Characters.

Christian Murphy, Sudhir P. Mudur, Daniel Holden, Marc-André Carbonneau, Donya Ghafourzadeh, Andre Beauchamp

Proceedings of the MIG '20: Motion, 2020

2019

DReCon: data-driven responsive control of physics-based characters.

Kevin Bergamin, Simon Clavet, Daniel Holden, James Richard Forbes

ACM Trans. Graph., 2019

Subspace neural physics: fast data-driven interactive simulation.

Daniel Holden, Bang Chi Duong, Sayantan Datta, Derek Nowrouzezahrai

Proceedings of the 18th annual ACM SIGGRAPH/Eurographics Symposium on Computer Animation, 2019

Robust Marker Trajectory Repair for MOCAP using Kinematic Reference.

Maksym Perepichka, Daniel Holden, Sudhir P. Mudur, Tiberiu Popa

Proceedings of the Motion, Interaction and Games, 2019

2018

Robust solving of optical motion capture data by denoising.

Daniel Holden

ACM Trans. Graph., 2018

2017

Reducing animator keyframes

Daniel Holden

PhD thesis, 2017

Scanning and animating characters dressed in multiple-layer garments.

Pengpeng Hu, Taku Komura, Daniel Holden, Yueqi Zhong

Vis. Comput., 2017

Learning Inverse Rig Mappings by Nonlinear Regression.

Daniel Holden, Jun Saito, Taku Komura

IEEE Trans. Vis. Comput. Graph., 2017

Phase-functioned neural networks for character control.

Daniel Holden, Taku Komura, Jun Saito

ACM Trans. Graph., 2017

Fast Neural Style Transfer for Motion Data.

Daniel Holden, Ikhsanul Habibie, Ikuo Kusajima, Taku Komura

IEEE Computer Graphics and Applications, 2017

A Recurrent Variational Autoencoder for Human Motion Synthesis.

Ikhsanul Habibie, Daniel Holden, Jonathan Schwarz, Joe Yearsley, Taku Komura

Proceedings of the British Machine Vision Conference 2017, 2017

2016

A deep learning framework for character motion synthesis and editing.

Daniel Holden, Jun Saito, Taku Komura

ACM Trans. Graph., 2016

Neural network ambient occlusion.

Daniel Holden, Jun Saito, Taku Komura

Proceedings of the SIGGRAPH ASIA 2016, Macao, December 5-8, 2016 - Technical Briefs, 2016

2015

Learning motion manifolds with convolutional autoencoders.

Daniel Holden, Jun Saito, Taku Komura, Thomas Joyce

Proceedings of the SIGGRAPH Asia 2015 Technical Briefs, Kobe, Japan, November 2-6, 2015, 2015

Learning an inverse rig mapping for character animation.

Daniel Holden, Jun Saito, Taku Komura

Proceedings of the 14th ACM SIGGRAPH / Eurographics Symposium on Computer Animation, 2015

Carpet unrolling for character control on uneven terrain.

Mark Miller, Daniel Holden, Rami Ali Al-Ashqar, Christophe Dubach, Kenny Mitchell, Taku Komura

Proceedings of the 8th ACM SIGGRAPH Conference on Motion in Games, 2015