Computer Vision Datasets
A collection of datasets for training and evaluating computer vision models, including datasets for object detection, scene understanding, and navigation.
The Computer Vision Datasets collection provides a comprehensive set of high-quality datasets for training and evaluating computer vision models. Curated by the Computer Vision Lab at Cyrion Labs, these datasets cover a wide range of tasks, including object detection, scene understanding, navigation, and more.
Our datasets are designed to be diverse, representative, and challenging, helping researchers develop more robust and generalizable computer vision models. Each dataset includes detailed documentation, standardized formats, and evaluation protocols to facilitate research and benchmarking.
Key Datasets
- NavScenes: A large-scale dataset for navigation in diverse environments, including indoor and outdoor scenes, varying lighting conditions, and weather conditions.
- ObjectNet3D: A dataset of 3D object annotations in real-world scenes, with over 100,000 objects across 50 categories.
- SceneUnderstanding: A dataset for holistic scene understanding, including semantic segmentation, depth estimation, and object relationships.
- AdverseWeather: A dataset of images captured in challenging weather conditions, including rain, fog, snow, and low light.
- MultiSensorFusion: A dataset with synchronized data from multiple sensors, including cameras, LiDAR, radar, and GPS.
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