1 code implementation • 16 Aug 2022 • Vikram Voleti, Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Louis-Simon Ménard, Christopher Pal
Inverse Kinematics (IK) systems are often rigid with respect to their input character, thus requiring user intervention to be adapted to new skeletons.
1 code implementation • 18 Jan 2022 • Boris N. Oreshkin, Antonios Valkanas, Félix G. Harvey, Louis-Simon Ménard, Florent Bocquelet, Mark J. Coates
We show that the task of synthesizing human motion conditioned on a set of key frames can be solved more accurately and effectively if a deep learning based interpolator operates in the delta mode using the spherical linear interpolator as a baseline.
Ranked #1 on Motion Synthesis on LaFAN1
1 code implementation • ICLR 2022 • Boris N. Oreshkin, Florent Bocquelet, Félix G. Harvey, Bay Raitt, Dominic Laflamme
Our work focuses on the development of a learnable neural representation of human pose for advanced AI assisted animation tooling.
1 code implementation • 9 Feb 2021 • Félix G. Harvey, Mike Yurick, Derek Nowrouzezahrai, Christopher Pal
To quantitatively evaluate performance on transitions and generalizations to longer time horizons, we present well-defined in-betweening benchmarks on a subset of the widely used Human3. 6M dataset and on LaFAN1, a novel high quality motion capture dataset that is more appropriate for transition generation.
Ranked #3 on Motion Synthesis on LaFAN1
no code implementations • NeurIPS 2020 • Julien Roy, Paul Barde, Félix G. Harvey, Derek Nowrouzezahrai, Christopher Pal
Finally, we analyze the effects of our proposed methods on the policies that our agents learn and show that our methods successfully enforce the qualities that we propose as proxies for coordinated behaviors.
2 code implementations • 4 Oct 2018 • Félix G. Harvey, Christopher Pal
Manually authoring transition animations for a complete locomotion system can be a tedious and time-consuming task, especially for large games that allow complex and constrained locomotion movements, where the number of transitions grows exponentially with the number of states.
no code implementations • 20 Nov 2015 • Félix G. Harvey, Julien Roy, David Kanaa, Christopher Pal
We find that using such constraints allow to stabilize the training of recurrent adversarial architectures for animation generation.