136 papers with code • 0 benchmarks • 12 datasets
These leaderboards are used to track progress in motion prediction
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.
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.
Shifts: A Dataset of Real Distributional Shift Across Multiple Large-Scale Tasks
However, many tasks of practical interest have different modalities, such as tabular data, audio, text, or sensor data, which offer significant challenges involving regression and discrete or continuous structured prediction.
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.
Peeking into the Future: Predicting Future Person Activities and Locations in Videos
To facilitate the training, the network is learned with an auxiliary task of predicting future location in which the activity will happen.