KITTI Dataset provides a suite of real-world computer vision benchmarks for autonomous driving research and development.
nuScenes is a public large-scale dataset for autonomous driving, providing a comprehensive suite of sensor data and annotations.
A dataset for commonsense NLI, challenging NLP models to understand and complete sentences in a human-like manner.
ShapeNet is a richly-annotated, large-scale dataset of 3D shapes designed to enable research in computer graphics, computer vision, robotics, and related disciplines.
Cityscapes is a large-scale dataset for semantic urban scene understanding, providing high-quality pixel-level annotations of street scenes from 50 different cities.
A collaborative release of open source dataset by Google for computer vision research, offering annotated images for object detection, segmentation, and visual relationship detection.
The Universe of 3D Objects: A massive open-source dataset for next-generation 3D generative AI and robotics.
SNLI is a large, annotated corpus for learning natural language inference, providing a benchmark for evaluating text representation systems.
