Human motion prediction

26 papers with code • 0 benchmarks • 2 datasets

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Greatest papers with code

On human motion prediction using recurrent neural networks

facebookresearch/QuaterNet 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.

Human motion prediction Motion Estimation +2

Peeking into the Future: Predicting Future Person Activities and Locations in Videos

google/next-prediction CVPR 2019

To facilitate the training, the network is learned with an auxiliary task of predicting future location in which the activity will happen.

Future prediction Human motion prediction +4

Long-term Human Motion Prediction with Scene Context

ZheC/GTA-IM-Dataset ECCV 2020

Human movement is goal-directed and influenced by the spatial layout of the objects in the scene.

Human motion prediction motion prediction

The Garden of Forking Paths: Towards Multi-Future Trajectory Prediction

JunweiLiang/Multiverse CVPR 2020

The first contribution is a new dataset, created in a realistic 3D simulator, which is based on real world trajectory data, and then extrapolated by human annotators to achieve different latent goals.

Autonomous Driving Human motion prediction +5

Learning Trajectory Dependencies for Human Motion Prediction

wei-mao-2019/LearnTrajDep ICCV 2019

In this paper, we propose a simple feed-forward deep network for motion prediction, which takes into account both temporal smoothness and spatial dependencies among human body joints.

Human motion prediction Human Pose Forecasting +2

Social Ways: Learning Multi-Modal Distributions of Pedestrian Trajectories with GANs

amiryanj/socialways CVPR 2019

We show through experiments on real and synthetic data that the proposed method leads to generate more diverse samples and to preserve the modes of the predictive distribution.

 Ranked #1 on Trajectory Prediction on Stanford Drone (FDE (in world coordinates) metric)

Human motion prediction Multi-future Trajectory Prediction +3

Dynamic Multiscale Graph Neural Networks for 3D Skeleton Based Human Motion Prediction

limaosen0/DMGNN CVPR 2020

The core idea of DMGNN is to use a multiscale graph to comprehensively model the internal relations of a human body for motion feature learning.

Human motion prediction motion prediction

Dynamic Multiscale Graph Neural Networks for 3D Skeleton-Based Human Motion Prediction

limaosen0/DMGNN 17 Mar 2020

The core idea of DMGNN is to use a multiscale graph to comprehensively model the internal relations of a human body for motion feature learning.

3D Human Pose Estimation 3D Pose Estimation +2

DAG-Net: Double Attentive Graph Neural Network for Trajectory Forecasting

alexmonti19/dagnet 26 May 2020

Understanding human motion behaviour is a critical task for several possible applications like self-driving cars or social robots, and in general for all those settings where an autonomous agent has to navigate inside a human-centric environment.

 Ranked #1 on Trajectory Prediction on Stanford Drone (ADE (in world coordinates) metric)

Human motion prediction Multi-future Trajectory Prediction +3

DLow: Diversifying Latent Flows for Diverse Human Motion Prediction

Khrylx/DLow ECCV 2020

To obtain samples from a pretrained generative model, most existing generative human motion prediction methods draw a set of independent Gaussian latent codes and convert them to motion samples.

Human motion prediction Human Pose Forecasting +1