Human Pose Forecasting
6 papers with code • 1 benchmarks • 2 datasets
Human pose forecasting is the task of detecting and predicting future human poses.
( Image credit: EgoPose )
Benchmarks
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PATS
Greatest papers with code
Structural-RNN: Deep Learning on Spatio-Temporal Graphs
The proposed method is generic and principled as it can be used for transforming any spatio-temporal graph through employing a certain set of well defined steps.
Ranked #4 on
Skeleton Based Action Recognition
on CAD-120
Learning Trajectory Dependencies for Human Motion Prediction
wei-mao-2019/LearnTrajDep
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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.
Ranked #1 on
Human Pose Forecasting
on Human3.6M
Ego-Pose Estimation and Forecasting as Real-Time PD Control
We propose the use of a proportional-derivative (PD) control based policy learned via reinforcement learning (RL) to estimate and forecast 3D human pose from egocentric videos.
DLow: Diversifying Latent Flows for Diverse Human Motion Prediction
Khrylx/DLow
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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.
Learning to Forecast and Refine Residual Motion for Image-to-Video Generation
We consider the problem of image-to-video translation, where an input image is translated into an output video containing motions of a single object.
Action-Agnostic Human Pose Forecasting
eddyhkchiu/pose_forecast_wacv
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In this paper, we propose a new action-agnostic method for short- and long-term human pose forecasting.
Ranked #3 on
Human Pose Forecasting
on Human3.6M