autonomous-driving
PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios
Dataset Description:
PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios is a large-scale synthetic video dataset of autonomous-driving scenes generated with NVIDIA's internal Omniverse simulation platform. Each clip is a temporally consistent multi-camera surround capture of one ego vehicle and surrounding traffic participants, paired with per-camera VLM captions. The dataset is designed to fill gaps in real-world driving data along two axes: (1) targeted long-tail… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/PhysicalAI-WorldModel-Synthetic-Autonomous-Driving-Scenarios.minuszero-indian-autonomous-driving-dataset-v2
INDUS-AD: Indian Dataset of Unstructured Urban Scenes for Autonomous Driving
Overview
INDUS-AD is the largest publicly released Indian autonomous-driving dataset for end-to-end autonomous-driving research. Its name expands to Indian Dataset of Unstructured Urban Scenes for Autonomous Driving.
This gated dataset is the decoded companion to the Minus Zero Indian Urban Autonomous Driving Dataset. It provides directly usable camera MP4s, normalized sensor tables… See the full description on the dataset page: https://huggingface.co/datasets/gagandeepreehal/minuszero-indian-autonomous-driving-dataset-v2.cmht-autonomous-driving
Dataset Card for CMHT Autonomous Driving Multimodal (MCAP)
This is a FiftyOne dataset with 4 samples.
Installation
If you haven't already, install FiftyOne:
pip install -U fiftyone
Usage
import fiftyone as fo
from fiftyone.utils.huggingface import load_from_hub
# Load the dataset
# Note: other available arguments include 'max_samples', etc
dataset = load_from_hub("Voxel51/cmht-autonomous-driving")
# Launch the App
session =… See the full description on the dataset page: https://huggingface.co/datasets/Voxel51/cmht-autonomous-driving.MIST-autonomous-driving-dataset
🛣️MIST
Multi-Domain Synthetic Dataset for Rural Driving🌾
🤗 Hugging Face
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📄 Paper(coming soon)
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💻 Code(coming soon)
🚗 Simulator (slowroads.io)
📘Dataset Introduction
MIST is a large-scale multi-domain synthetic dataset designed for rural driving scenarios.
It provides explicitly structured domain factors—season, time of day, and weather—forming 32 balanced domain configurations.… See the full description on the dataset page: https://huggingface.co/datasets/jongwonryu/MIST-autonomous-driving-dataset.minuszero-indian-autonomous-driving-dataset
Minus Zero Indian Urban Autonomous Driving Dataset
Overview
This dataset provides original multicamera autonomous-driving recordings in MCAP format. It is designed for non-commercial research on surround-view perception, temporal and cross-camera synchronization, H.265 video pipelines, localization, GNSS/pose integration, and robotics data tooling.
Recordings include camera and GNSS/pose streams, with machine-state telemetry present in a small subset. Camera… See the full description on the dataset page: https://huggingface.co/datasets/gagandeepreehal/minuszero-indian-autonomous-driving-dataset.autonomous-driving-carla
CARLA Autonomous Driving Dataset
Custom datasets for autonomous driving in CARLA simulator
Created for CMPE 789 - Robot Perception at Rochester Institute of Technology
📊 Dataset Overview
This repository contains two custom-generated datasets from the CARLA 0.9.15 simulator for training autonomous driving perception models:
Dataset
Task
Images
Format
Size
YOLO Dataset
Object Detection
4,000
YOLOv8/v11
~1.2 GB
UFLD Dataset
Lane Detection
10,000… See the full description on the dataset page: https://huggingface.co/datasets/jkdxbns/autonomous-driving-carla.