25 datasets found

The dataset used in the paper is a synthetic dataset for trajectory prediction and lane change prediction.

A large-scale dataset and models for pedestrian intention estimation and trajectory prediction.

The Talk2Car dataset is a benchmark for language grounding for autonomous vehicles. It contains images of urban scenes and natural language commands referring to objects in the...

The dataset used in this paper is a trajectory predictor from a developmental commercial flight management system.

The nuScenes dataset is a large-scale dataset for autonomous driving, containing 100,000 scenes with 10 Hz sampling frequency.

The Apolloscape dataset is a large-scale dataset for autonomous driving, containing 75 scenarios with 10 Hz sampling frequency.

The UCY/ETH dataset contains real pedestrian trajectories at five different locations captured at 2.5 Hz.

Road user trajectory prediction in dynamic environments is a challenging but crucial task for various applications, such as autonomous driving. One of the main challenges in...

This paper introduces STAR, a framework for spatio-temporal crowd trajectory prediction with only attention mechanisms.

The INTERACTION dataset is a highly interactive driving dataset containing merges, roundabouts, and intersections.

The rounD dataset contains trajectories from various locations in Germany captured at a frequency of 25 Hz.

A drone dataset of naturalistic vehicle trajectories on German highways for validation of highly automated driving systems.

The Trajnet++ benchmark provides a fixed data split and unified pre-processing for these datasets.

Trajectory prediction is a crucial task for the safe operation of an autonomous vehicle. The task is known as human trajectory prediction and aims to predict the future...

Trajectory prediction plays an essential role in autonomous vehicles. While numerous strategies have been developed to enhance the robustness of trajectory prediction models,...

The Stanford Drone Dataset (SDD) is a large-scale dataset that consists of 60 aerial-view videos captured by drones over Stanford University. SDD contains positions of more than...

The ETH-UCY dataset consists of ETH, Hotel, Univ, Zara1, and Zara2 outdoor scenes captured from a bird’s-eye view. All scenes contain human trajectories in urban scenes....

Forecasting human trajectories in traffic scenes is critical for safety within mixed or fully autonomous systems. Human future trajectories are driven by two major stimuli,...

Pedestrian trajectory prediction is an important component in a range of applications such as social robots and self-driving vehicles, and plays a key role in understanding...

Pedestrian trajectory forecasting is a fundamental task in multiple utility areas, such as self-driving, autonomous robots, and surveillance systems. The future trajectory...