Motion Forecasting
66 papers with code • 1 benchmarks • 12 datasets
Motion forecasting is the task of predicting the location of a tracked object in the future
Benchmarks
These leaderboards are used to track progress in Motion Forecasting
| Trend | Dataset | Best Model | Paper | Code | Compare |
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Datasets
Argoverse
Waymo Open Motion Dataset
Argoverse-HD
Argoverse 2 Motion Forecasting
SinD
Argoverse 2 Sensor
Lyft Level 5 Prediction
Argoverse 2 Lidar
Latest papers with no code
SSL-Interactions: Pretext Tasks for Interactive Trajectory Prediction
This paper addresses motion forecasting in multi-agent environments, pivotal for ensuring safety of autonomous vehicles.
Sim-to-Real Causal Transfer: A Metric Learning Approach to Causally-Aware Interaction Representations
Modeling spatial-temporal interactions among neighboring agents is at the heart of multi-agent problems such as motion forecasting and crowd navigation.
Personalized Pose Forecasting
Human pose forecasting is the task of predicting articulated human motion given past human motion.
FFINet: Future Feedback Interaction Network for Motion Forecasting
In this paper, we propose a novel Future Feedback Interaction Network (FFINet) to aggregate features the current observations and potential future interactions for trajectory prediction.
OSM vs HD Maps: Map Representations for Trajectory Prediction
While High Definition (HD) Maps have long been favored for their precise depictions of static road elements, their accessibility constraints and susceptibility to rapid environmental changes impede the widespread deployment of autonomous driving, especially in the motion forecasting task.
EqDrive: Efficient Equivariant Motion Forecasting with Multi-Modality for Autonomous Driving
Forecasting vehicular motions in autonomous driving requires a deep understanding of agent interactions and the preservation of motion equivariance under Euclidean geometric transformations.
KI-PMF: Knowledge Integrated Plausible Motion Forecasting
Accurately forecasting the motion of traffic actors is crucial for the deployment of autonomous vehicles at a large scale.
The WayHome: Long-term Motion Prediction on Dynamically Scaled
One of the key challenges for autonomous vehicles is the ability to accurately predict the motion of other objects in the surrounding environment, such as pedestrians or other vehicles.
Scene-aware Human Motion Forecasting via Mutual Distance Prediction
In this paper, we tackle the problem of scene-aware 3D human motion forecasting.
MotionLM: Multi-Agent Motion Forecasting as Language Modeling
Here, we represent continuous trajectories as sequences of discrete motion tokens and cast multi-agent motion prediction as a language modeling task over this domain.
