Cityscapes Dataset
Cityscapes is a large-scale dataset for semantic urban scene understanding, providing high-quality pixel-level annotations of street scenes from 50 different cities.
Cityscapes is a large-scale dataset for semantic urban scene understanding, providing high-quality pixel-level annotations of street scenes from 50 different cities.

The Universe of 3D Objects: A massive open-source dataset for next-generation 3D generative AI and robotics.
The VCTK Corpus provides diverse English speech data from 110 speakers, ideal for voice cloning and speech synthesis research.
The modern drop-in replacement for the original MNIST dataset for computer vision benchmarking.
A comprehensive benchmark for multi-attribute fashion classification and visual search optimization.
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 gold standard for frame-semantic annotation and computational lexical relations.
ShapeNet is a richly-annotated, large-scale dataset of 3D shapes designed to enable research in computer graphics, computer vision, robotics, and related disciplines.
SNLI is a large, annotated corpus for learning natural language inference, providing a benchmark for evaluating text representation systems.
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.