motion prediction
190 papers with code • 0 benchmarks • 13 datasets
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Libraries
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Most implemented papers
Tracking without bells and whistles
Therefore, we motivate our approach as a new tracking paradigm and point out promising future research directions.
On human motion prediction using recurrent neural networks
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.
GRIP++: Enhanced Graph-based Interaction-aware Trajectory Prediction for Autonomous Driving
Despite the advancement in the technology of autonomous driving cars, the safety of a self-driving car is still a challenging problem that has not been well studied.
Learning Trajectory Dependencies for Human Motion Prediction
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
Our model, which we call HP-GAN, learns a probability density function of future human poses conditioned on previous poses.
BiHMP-GAN: Bidirectional 3D Human Motion Prediction GAN
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.
Social-STGCNN: A Social Spatio-Temporal Graph Convolutional Neural Network for Human Trajectory Prediction
Better machine understanding of pedestrian behaviors enables faster progress in modeling interactions between agents such as autonomous vehicles and humans.
One Thousand and One Hours: Self-driving Motion Prediction Dataset
Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to date, containing over 1, 000 hours of data.
History Repeats Itself: Human Motion Prediction via Motion Attention
Human motion prediction aims to forecast future human poses given a past motion.
Scene Transformer: A unified architecture for predicting multiple agent trajectories
In this work, we formulate a model for predicting the behavior of all agents jointly, producing consistent futures that account for interactions between agents.