Computer Vision in Autonomous Vehicles
Get your AI on the road faster. FiftyOne uses computer vision to accelerate development of autonomous and driver assistance solutions. By systematically curating datasets and analyzing model performance, your team can reduce development time and improve real-world accuracy.
Benefits of CV for autonomous vehicles
Unlock your AI’s full potential with systematic data analysis
From ADAS to driver monitoring and more, data quality makes or breaks AI model performance. FiftyOne helps you curate high-quality datasets, analyze data and model results, and streamline development; turning R&D into real-world self-driving car success.
Physical AI Workbench
Build neural reconstructions on a foundation of high-quality data
The most advanced simulations depend on high quality data. The Physical AI Workbench accelerates computer vision in autonomous vehicles by generating accurate and validated sim-ready datasets; so every compute dollar yields usable results.
CV use cases for autonomous vehicles
Power any CV use case for autonomous vehicles
Computer vision plays a critical role in a wide variety of automotive use cases. That’s why leaders and innovators building solutions rely on FiftyOne.
Lane and object detection: Enhance the ability to detect and follow traffic lanes in tough conditions by quickly spotting gaps and outliers in training data and model results.
In-cabin analytics: Deliver new safety and improved driver experiences by using data insights to build reliable detection and analysis models.
Multi-camera sensor fusion: Group together visual data samples from multiple sensors and locations to create a better understanding of dynamic environments.
Lidar and radar point clouds: Build advanced solutions by being able to easily explore and visualize 3D data from multiple angles and sources.
Semantic segmentation: Analyze and improve perception of roads, obstacles, pedestrians, signs, and more to ensure safe navigation.
Video object tracking: Visualize videos, ground truth detections, and predicted trajectories to gain insights into your data and evaluate model accuracy.
Self driving machine learning features
How visual AI supports automotive CV and self-driving AI
Unify multimodal data
- Pinpoint samples of interest
- Annotation workflows
- Continuous improvement
Manage millions of multimodal samples through a united interface
Hands-free driving systems and vehicles rely on massive amounts of data. FiftyOne makes it easy to manage your samples across dozens of formats.
- Multimodal datasets: images, videos, clips, frames, geolocation, and 3D lidar and radar point clouds
- Any metadata you need: time of day, camera or device ID, location information, weather conditions, and anything else you need in your AI workflows
- Any model you’re working with: lane detection, object detection, semantic segmentation, and many more
Quickly find the subsets of data you want
Sifting through massive amounts of data is like searching for a needle in a haystack. Pinpoint samples of interest in seconds using FiftyOne.
- Create meaningful, balanced datasets: query samples by metadata to correct for imbalances
- Accelerate training data selection: quickly find unique scenarios and anomalies in your data streams
- Cover the edge cases: identify hard samples to strengthen your datasets and model performance
Only annotate what you need
Generating annotations can be complex, cumbersome, and costly. FiftyOne integrates with your favorite annotation tools to become your mission control for annotation workflows.
- Stop passing data around: collaborate with teammates and vendors on a single source of truth
- Stop overpaying for annotations: identify your most valuable samples to annotate, then automatically send them to your annotation vendor
- Mitigate annotation mistakes: assess the quality of your annotations to improve both your datasets and models
Continuously build models that perform
Model training is never truly complete. With FiftyOne's continuous analysis and embedding-based diagnostics, you can quickly discover and address weaknesses in your data, refining your model iteratively for maximum accuracy.
- Understand your model’s failure modes: browse model performance at the sample level so you can take the right steps to address failures
- Embrace continuous evaluation: integrate FiftyOne into your training pipeline to evaluate and improve model performance and datasets with every model update
- Manage dataset versions: track revisions to your datasets so you can view or rollback to previous versions of your datasets at any time
Increase productivity and efficiency
Automate dozens of computer vision workflows with FiftyOne so you can free up valuable engineering time and focus on what matters most.
Deliver features and innovations faster
Shave months of development time off your vision-based AI projects by using FiftyOne to accelerate data curation and model evaluation.
Save money on your tech stack
Avoid the unnecessary costs of manual data wrangling and overpaying for annotation and data collection by using FiftyOne to streamline and automate how you work with data.
Automotive computer vision features
Designed for AI builders
FiftyOne natively supports and enables the computer vision building blocks needed to develop robust automotive AI solutions.
- Classification
- Detection
- Segmentation
- Polygons and polylines
- Keypoints
- Pointclouds
- Heatmaps
- Geolocation
- Embeddings
- Multiview datasets
- Images, videos, and 3D data
“From vehicle safety and autonomy to security systems to robotics, Bosch is a leader in artificial intelligence solutions utilizing computer vision. Voxel51’s solutions help us organize, evaluate and refine our data and models, enabling us to develop robust, reliable AI applications across multiple teams and projects.”
Arvind Kumar Shekar
Lead Expert AI Validation, Bosch
Computer vision resources
Learn more about visual AI in automotive
Learn how visual AI is increasing safety, autonomy, and efficiency in automotive and mobility applications.
How to Make the Best Self-Driving Dataset
In the race to safely release fully autonomous vehicles, understanding self-driving datasets is key. Learn more about the tools and techniques shaping the future of self-driving technology.
Data eats models for lunch
Talk to our computer vision experts to start building better datasets and models.