Human motion prediction

55 papers with code • 0 benchmarks • 4 datasets

Action prediction is a pre-fact video understanding task, which focuses on future states, in other words, it needs to reason about future states or infer action labels before the end of action execution.

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.

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.

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.

History Repeats Itself: Human Motion Prediction via Motion Attention

wei-mao-2019/HisRepItself ECCV 2020

Human motion prediction aims to forecast future human poses given a past motion.

BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN

maharshi95/Pose2vec 6 Dec 2018

The discriminator is trained also to regress this extrinsic factor r, which is used alongside with the intrinsic factor (encoded starting pose sequence) to generate a particular pose sequence.

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.

Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction

abduallahmohamed/Social-STGCNN CVPR 2020

Better machine understanding of pedestrian behaviors enables faster progress in modeling interactions between agents such as autonomous vehicles and humans.

Generative Model-Enhanced Human Motion Prediction

bouracha/OoDMotion 5 Oct 2020

The task of predicting human motion is complicated by the natural heterogeneity and compositionality of actions, necessitating robustness to distributional shifts as far as out-of-distribution (OoD).

Diverse Human Motion Prediction via Gumbel-Softmax Sampling from an Auxiliary Space

droliven/diverse_sampling 15 Jul 2022

In this paper, we propose a novel sampling strategy for sampling very diverse results from an imbalanced multimodal distribution learned by a deep generative model.

Complex Gated Recurrent Neural Networks

v0lta/Complex-gated-recurrent-neural-networks NeurIPS 2018

Complex numbers have long been favoured for digital signal processing, yet complex representations rarely appear in deep learning architectures.