About CVAT.AI

Provides a cloud-based and self-hosted data annotation platform designed for computer vision tasks, supporting formats like COCO, YOLO, and PASCAL VOC. It streamlines the creation of labeled datasets by integrating AI-powered auto-annotation, advanced tools for bounding boxes, segmentation, and 3D cuboids, and analytics for tracking annotator productivity, enabling faster and more accurate model training.

<problem> Creating high-quality, labeled datasets for computer vision tasks is often time-consuming and requires specialized tools. Existing annotation platforms can be difficult to set up, lack key features, or are cost-prohibitive for many organizations. This creates a bottleneck in the machine learning pipeline, slowing down model training and deployment. </problem> <solution> CVAT is a data annotation platform designed to streamline the creation of labeled datasets for computer vision. It offers both a cloud-based and self-hosted solution, providing flexibility for different project needs and security requirements. The platform supports a wide range of annotation formats, including COCO, YOLO, and PASCAL VOC, ensuring compatibility with various machine learning frameworks. CVAT integrates AI-powered auto-annotation to accelerate the labeling process, along with advanced tools for tasks such as bounding boxes, segmentation, and 3D cuboids. Management and analytics features provide insights into annotator productivity, enabling teams to optimize their workflows and improve data quality. </solution> <features> - AI-powered auto-annotation to speed up the labeling process - Support for bounding boxes, polygons, points, skeletons, cuboids, and trajectories - Cloud storage integration with AWS S3, Google Cloud Storage, and Azure Blob Storage - Algorithmic assistance tools like intelligent scissors and histogram equalization - Management and analytics dashboard for tracking annotator performance and project progress - Support for image classification, object detection, semantic segmentation, point clouds, 3D cuboids, video annotation, and skeleton annotation - Compatibility with 19 annotation formats, including PASCAL VOC, CVAT, YOLO, and COCO - Web-based interface accessible from any device with a browser - Options for both cloud-based (CVAT.ai) and on-premise deployment </features> <target_audience> CVAT is designed for machine learning engineers, data scientists, and annotation teams working on computer vision projects across various industries, including healthcare, retail, agriculture, automotive, and manufacturing. </target_audience>

What does CVAT.AI do?

When was CVAT.AI founded?

CVAT.AI was founded in 2022.

Founded

2022

Employees

77 employees

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CVAT.AI

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Executive Summary

cvat.ai 3K+

Founded 2022

Funding

No funding information available.

Team (75+)

No team information available.

Company Description

Problem

Creating high-quality, labeled datasets for computer vision tasks is often time-consuming and requires specialized tools. Existing annotation platforms can be difficult to set up, lack key features, or are cost-prohibitive for many organizations. This creates a bottleneck in the machine learning pipeline, slowing down model training and deployment.

Solution

CVAT is a data annotation platform designed to streamline the creation of labeled datasets for computer vision. It offers both a cloud-based and self-hosted solution, providing flexibility for different project needs and security requirements. The platform supports a wide range of annotation formats, including COCO, YOLO, and PASCAL VOC, ensuring compatibility with various machine learning frameworks. CVAT integrates AI-powered auto-annotation to accelerate the labeling process, along with advanced tools for tasks such as bounding boxes, segmentation, and 3D cuboids. Management and analytics features provide insights into annotator productivity, enabling teams to optimize their workflows and improve data quality.

Features

AI-powered auto-annotation to speed up the labeling process

Support for bounding boxes, polygons, points, skeletons, cuboids, and trajectories

Cloud storage integration with AWS S3, Google Cloud Storage, and Azure Blob Storage

Algorithmic assistance tools like intelligent scissors and histogram equalization

Management and analytics dashboard for tracking annotator performance and project progress

Support for image classification, object detection, semantic segmentation, point clouds, 3D cuboids, video annotation, and skeleton annotation

Compatibility with 19 annotation formats, including PASCAL VOC, CVAT, YOLO, and COCO

Web-based interface accessible from any device with a browser

Options for both cloud-based (CVAT.ai) and on-premise deployment

Target Audience

CVAT is designed for machine learning engineers, data scientists, and annotation teams working on computer vision projects across various industries, including healthcare, retail, agriculture, automotive, and manufacturing.