Trajectory Prediction
256 papers with code • 29 benchmarks • 34 datasets
Trajectory Prediction is the problem of predicting the short-term (1-3 seconds) and long-term (3-5 seconds) spatial coordinates of various road-agents such as cars, buses, pedestrians, rickshaws, and animals, etc. These road-agents have different dynamic behaviors that may correspond to aggressive or conservative driving styles.
Source: Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
Benchmarks
These leaderboards are used to track progress in Trajectory Prediction
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
Libraries
Use these libraries to find Trajectory Prediction models and implementationsDatasets
nuScenes
Argoverse
UCY
highD Dataset
INTERACTION Dataset
Waymo Open Motion Dataset
ApolloScape
ETH
inD Dataset
HDD
Latest papers
Social-Transmotion: Promptable Human Trajectory Prediction
vita-epfl/social-transmotion
•
•
We translate the idea of a prompt from Natural Language Processing (NLP) to the task of human trajectory prediction, where a prompt can be a sequence of x-y coordinates on the ground, bounding boxes in the image plane, or body pose keypoints in either 2D or 3D.
Improving Transferability for Cross-domain Trajectory Prediction via Neural Stochastic Differential Equation
To address this limitation, we propose a method based on continuous and stochastic representations of Neural Stochastic Differential Equations (NSDE) for alleviating discrepancies due to data acquisition strategy.
Multiple Hypothesis Dropout: Estimating the Parameters of Multi-Modal Output Distributions
dngu7/multiple-hypothesis-dropout
•
•
In many real-world applications, from robotics to pedestrian trajectory prediction, there is a need to predict multiple real-valued outputs to represent several potential scenarios.
nuScenes Knowledge Graph -- A comprehensive semantic representation of traffic scenes for trajectory prediction
boschresearch/nuscenes_knowledge_graph
•
•
Further, we present nuScenes Knowledge Graph (nSKG), a knowledge graph for the nuScenes dataset, that models explicitly all scene participants and road elements, as well as their semantic and spatial relationships.
World Models via Policy-Guided Trajectory Diffusion
marc-rigter/polygrad-world-models
•
•
Our results demonstrate that PolyGRAD outperforms state-of-the-art baselines in terms of trajectory prediction error for short trajectories, with the exception of autoregressive diffusion.
BAT: Behavior-Aware Human-Like Trajectory Prediction for Autonomous Driving
petrichor625/batraj-behavior-aware-model
•
•
The ability to accurately predict the trajectory of surrounding vehicles is a critical hurdle to overcome on the journey to fully autonomous vehicles.
Image and AIS Data Fusion Technique for Maritime Computer Vision Applications
This demonstrates the potential of our approach in creating datasets for vessel detection, pose estimation and auto-labelling pipelines.
STF: Spatial Temporal Fusion for Trajectory Prediction
pengqianhan/STF-Spatial-Temporal-Fusion-for-Trajectory-Prediction
•
•
The main reason is that the trajectory is a kind of complex data, including spatial and temporal information, which is crucial for accurate prediction.
Robust Conformal Prediction for STL Runtime Verification under Distribution Shift
To address these challenges, we assume to know an upper bound on the statistical distance (in terms of an f-divergence) between the distributions at deployment and design time, and we utilize techniques based on robust conformal prediction.
Latent Task-Specific Graph Network Simulators
philippdahlinger/ltsgns_ai4science
•
•
Movement primitives further allow us to accommodate various types of context data, as demonstrated through the utilization of point clouds during inference.
