Trajectory Prediction
255 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 with no code
An Animation-based Augmentation Approach for Action Recognition from Discontinuous Video
Action recognition, an essential component of computer vision, plays a pivotal role in multiple applications.
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.
TrajectoryNAS: A Neural Architecture Search for Trajectory Prediction
Through empirical studies, TrajectoryNAS demonstrates its effectiveness in enhancing the performance of autonomous driving systems, marking a significant advancement in the field. Experimental results reveal that TrajcetoryNAS yield a minimum of 4. 8 higger accuracy and 1. 1* lower latency over competing methods on the NuScenes dataset.
Informed Spectral Normalized Gaussian Processes for Trajectory Prediction
Previous work has shown that using such informative priors to regularize probabilistic deep learning (DL) models increases their performance and data-efficiency.
Intention-aware Denoising Diffusion Model for Trajectory Prediction
To decrease the inference time, we reduce the variable dimensions in the intention-aware diffusion process and restrict the initial distribution of the action-aware diffusion process, which leads to fewer diffusion steps.
Tractable Joint Prediction and Planning over Discrete Behavior Modes for Urban Driving
Although these models have conventionally been evaluated for open-loop prediction, we show that they can be used to parameterize autoregressive closed-loop models without retraining.
