Motion Synthesis

58 papers with code • 6 benchmarks • 8 datasets

Most implemented papers

On human motion prediction using recurrent neural networks

una-dinosauria/human-motion-prediction CVPR 2017

Human motion modelling is a classical problem at the intersection of graphics and computer vision, with applications spanning human-computer interaction, motion synthesis, and motion prediction for virtual and augmented reality.

DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills

xbpeng/DeepMimic 8 Apr 2018

We further explore a number of methods for integrating multiple clips into the learning process to develop multi-skilled agents capable of performing a rich repertoire of diverse skills.

HP-GAN: Probabilistic 3D human motion prediction via GAN

ebarsoum/hpgan 27 Nov 2017

Our model, which we call HP-GAN, learns a probability density function of future human poses conditioned on previous poses.

MoGlow: Probabilistic and controllable motion synthesis using normalising flows

chaiyujin/glow-pytorch 16 May 2019

Data-driven modelling and synthesis of motion is an active research area with applications that include animation, games, and social robotics.

Multi-View Motion Synthesis via Applying Rotated Dual-Pixel Blur Kernels

Abdullah-Abuolaim/defocus-deblurring-dual-pixel 15 Nov 2021

In this work, we follow the trend of rendering the NIMAT effect by introducing a modification on the blur synthesis procedure in portrait mode.

MeshTalk: 3D Face Animation from Speech using Cross-Modality Disentanglement

facebookresearch/meshtalk ICCV 2021

To improve upon existing models, we propose a generic audio-driven facial animation approach that achieves highly realistic motion synthesis results for the entire face.

Auto-Conditioned Recurrent Networks for Extended Complex Human Motion Synthesis

papagina/auto_conditioned_rnn_motion ICLR 2018

We present a real-time method for synthesizing highly complex human motions using a novel training regime we call the auto-conditioned Recurrent Neural Network (acRNN).

A Neural Temporal Model for Human Motion Prediction

cr7anand/neural_temporal_models CVPR 2019

We propose novel neural temporal models for predicting and synthesizing human motion, achieving state-of-the-art in modeling long-term motion trajectories while being competitive with prior work in short-term prediction and requiring significantly less computation.

Dancing to Music

NVlabs/Dance2Music NeurIPS 2019

In the analysis phase, we decompose a dance into a series of basic dance units, through which the model learns how to move.

CARL: Controllable Agent with Reinforcement Learning for Quadruped Locomotion

inventec-ai-center/carl-siggraph2020 7 May 2020

Motion synthesis in a dynamic environment has been a long-standing problem for character animation.