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2020 – today
- 2024
[c9]Alexander R. Farhang, Brendan Mulcahy, Daniel Holden, Iain Matthews, Yisong Yue:
Humanlike Behavior in a Third-Person Shooter with Imitation Learning. CoG 2024: 1-4- [i2]Shashank Tripathi, Omid Taheri, Christoph Lassner, Michael J. Black, Daniel Holden, Carsten Stoll:
HUMOS: Human Motion Model Conditioned on Body Shape. CoRR abs/2409.03944 (2024) - 2023
- [j11]Saeed Ghorbani
, Ylva Ferstl, Daniel Holden, Nikolaus F. Troje, Marc-André Carbonneau:
ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech. Comput. Graph. Forum 42(1): 206-216 (2023) - 2022
- [i1]Saeed Ghorbani, Ylva Ferstl, Daniel Holden, Nikolaus F. Troje, Marc-André Carbonneau:
ZeroEGGS: Zero-shot Example-based Gesture Generation from Speech. CoRR abs/2209.07556 (2022) - 2021
- [j10]Christian Murphy, Sudhir P. Mudur, Daniel Holden, Marc-André Carbonneau, Donya Ghafourzadeh, Andre Beauchamp:
Artist guided generation of video game production quality face textures. Comput. Graph. 98: 268-279 (2021) - [j9]Levi Fussell, Kevin Bergamin, Daniel Holden:
SuperTrack: motion tracking for physically simulated characters using supervised learning. ACM Trans. Graph. 40(6): 197:1-197:13 (2021) - 2020
- [j8]Daniel Holden, Oussama Kanoun, Maksym Perepichka, Tiberiu Popa:
Learned motion matching. ACM Trans. Graph. 39(4): 53 (2020) - [c8]Christian Murphy, Sudhir P. Mudur, Daniel Holden, Marc-André Carbonneau, Donya Ghafourzadeh, Andre Beauchamp:
Appearance Controlled Face Texture Generation for Video Game Characters. MIG 2020: 9:1-9:11 - [e2]Daniel Holden:
19th ACM SIGGRAPH / Eurographics Symposium on Computer Animation 2020, SCA 2020 - Showcases, Online, October 6-9, 2020. Eurographics Association 2020, ISBN 978-3-03868-129-8 [contents]
2010 – 2019
- 2019
- [j7]Kevin Bergamin, Simon Clavet, Daniel Holden, James Richard Forbes:
DReCon: data-driven responsive control of physics-based characters. ACM Trans. Graph. 38(6): 206:1-206:11 (2019) - [c7]Maksym Perepichka, Daniel Holden, Sudhir P. Mudur, Tiberiu Popa:
Robust Marker Trajectory Repair for MOCAP using Kinematic Reference. MIG 2019: 9:1-9:10 - [c6]Daniel Holden, Bang Chi Duong, Sayantan Datta, Derek Nowrouzezahrai:
Subspace neural physics: fast data-driven interactive simulation. Symposium on Computer Animation 2019: 6:1-6:12 - [e1]Hubert P. H. Shum, Edmond S. L. Ho, Marie-Paule Cani, Tiberiu Popa, Daniel Holden, He Wang:
Motion, Interaction and Games, MIG 2019, Newcastle upon Tyne, UK, October 28-30, 2019. ACM 2019, ISBN 978-1-4503-6994-7 [contents] - 2018
- [j6]Daniel Holden:
Robust solving of optical motion capture data by denoising. ACM Trans. Graph. 37(4): 165 (2018) - 2017
- [b1]Daniel Holden:
Reducing animator keyframes. University of Edinburgh, UK, 2017 - [j5]Daniel Holden, Ikhsanul Habibie, Ikuo Kusajima, Taku Komura:
Fast Neural Style Transfer for Motion Data. IEEE Computer Graphics and Applications 37(4): 42-49 (2017) - [j4]Daniel Holden, Taku Komura, Jun Saito:
Phase-functioned neural networks for character control. ACM Trans. Graph. 36(4): 42:1-42:13 (2017) - [j3]Daniel Holden, Jun Saito, Taku Komura:
Learning Inverse Rig Mappings by Nonlinear Regression. IEEE Trans. Vis. Comput. Graph. 23(3): 1167-1178 (2017) - [j2]Pengpeng Hu, Taku Komura, Daniel Holden, Yueqi Zhong:
Scanning and animating characters dressed in multiple-layer garments. Vis. Comput. 33(6-8): 961-969 (2017) - [c5]Ikhsanul Habibie, Daniel Holden, Jonathan Schwarz, Joe Yearsley, Taku Komura:
A Recurrent Variational Autoencoder for Human Motion Synthesis. BMVC 2017 - 2016
- [j1]Daniel Holden, Jun Saito, Taku Komura:
A deep learning framework for character motion synthesis and editing. ACM Trans. Graph. 35(4): 138:1-138:11 (2016) - [c4]Daniel Holden, Jun Saito, Taku Komura:
Neural network ambient occlusion. SIGGRAPH Asia Technical Briefs 2016: 9 - 2015
- [c3]Mark Miller, Daniel Holden, Rami Ali Al-Ashqar, Christophe Dubach, Kenny Mitchell, Taku Komura:
Carpet unrolling for character control on uneven terrain. MIG 2015: 193-198 - [c2]Daniel Holden, Jun Saito, Taku Komura:
Learning an inverse rig mapping for character animation. Symposium on Computer Animation 2015: 165-173 - [c1]Daniel Holden, Jun Saito, Taku Komura, Thomas Joyce:
Learning motion manifolds with convolutional autoencoders. SIGGRAPH Asia Technical Briefs 2015: 18:1-18:4
Coauthor Index
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last updated on 2024-10-10 22:19 CEST by the dblp team
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