Trajectory Prediction
251 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
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Libraries
Use these libraries to find Trajectory Prediction models and implementationsDatasets
nuScenes
Argoverse
UCY
highD Dataset
INTERACTION Dataset
ApolloScape
Waymo Open Motion Dataset
ETH
inD Dataset
HDD
Latest papers with no code
uTRAND: Unsupervised Anomaly Detection in Traffic Trajectories
Deep learning-based approaches have achieved significant improvements on public video anomaly datasets, but often do not perform well in real-world applications.
S4TP: Social-Suitable and Safety-Sensitive Trajectory Planning for Autonomous Vehicles
To effectively assess the risks prevailing in the vicinity of AVs in social interactive traffic scenarios and achieve safe autonomous driving, this article proposes a social-suitable and safety-sensitive trajectory planning (S4TP) framework.
TrACT: A Training Dynamics Aware Contrastive Learning Framework for Long-tail Trajectory Prediction
In this paper, we propose to incorporate richer training dynamics information into a prototypical contrastive learning framework.
PreGSU-A Generalized Traffic Scene Understanding Model for Autonomous Driving based on Pre-trained Graph Attention Network
In this study, we propose PreGSU, a generalized pre-trained scene understanding model based on graph attention network to learn the universal interaction and reasoning of traffic scenes to support various downstream tasks.
Let It Flow: Simultaneous Optimization of 3D Flow and Object Clustering
We identified the structural constraints and the use of large and strict rigid clusters as the main pitfall of the current approaches and we propose a novel clustering approach that allows for combination of overlapping soft clusters as well as non-overlapping rigid clusters representation.
Generating Synthetic Ground Truth Distributions for Multi-step Trajectory Prediction using Probabilistic Composite Bézier Curves
An appropriate data basis grants one of the most important aspects for training and evaluating probabilistic trajectory prediction models based on neural networks.
Adapting to Length Shift: FlexiLength Network for Trajectory Prediction
Trajectory prediction plays an important role in various applications, including autonomous driving, robotics, and scene understanding.
Egocentric Scene-aware Human Trajectory Prediction
Wearable collaborative robots stand to assist human wearers who need fall prevention assistance or wear exoskeletons.
Solution for Point Tracking Task of ICCV 1st Perception Test Challenge 2023
To address this issue, we propose a simple yet effective approach called TAP with confident static points (TAPIR+), which focuses on rectifying the tracking of the static point in the videos shot by a static camera.
Certified Human Trajectory Prediction
Trajectory prediction plays an essential role in autonomous vehicles.
