CVAT vs Deepen AI

CVAT turns images, video, 3D data and audio into labeled datasets for AI workflows. Its annotation tools include boxes, masks, polygons, keypoints, skeletons and object tracks, with additional listed types such as cuboids, ellipses and tags. Teams can review jobs through validation and acceptance stages and assess quality using ground truth, honeypots and consensus workflows. Storage connections include Amazon S3, Azure Blob Storage, Google Cloud Storage, compatible buckets and self-hosted storage. CVAT names SAM 2, SAM 3, Ultralytics, Hugging Face and custom models as labeling aids. It exports to more than 20 formats, including COCO, YOLO, KITTI, Cityscapes and Pascal VOC, and offers API, SDK and CLI automation. Deployment can be managed in the cloud or self-hosted, including on-premises and air-gapped options. Free plans are available; online paid plans start at $23/user/mo billed annually. CVAT lists security controls but says it does not hold ISO 27001 or SOC 2 certifications.

Deepen AI provides connected data infrastructure for Physical AI, linking sensor calibration, capture, curation, annotation, and validation. Deepen Calibrate aligns camera, LiDAR, radar, and IMU sensors to a shared frame; the site reports under 0.8-pixel reprojection error and sub-1° angular error. Deepen Curate deduplicates sensor data, searches clips and frames, and surfaces rare or long-tail scenarios before labeling. Deepen Annotate handles 2D and 3D labels, including boxes, segmentation, keypoints, point clouds, and multi-frame tracking. Deepen Validate scores scenario coverage, audits and compares labels, prioritizes risky frames for review, and records signed audit trails. REST APIs and SDKs connect products to customer pipelines. Supported formats include ROS 2, MCAP, nuScenes, HDF5, Parquet, COCO, Rosbag, Zarr, KITTI, ORC, Pascal, WebDataset, and ASAM OpenLABEL. Deployment spans managed cloud, VPC, on-premises, and air-gapped environments. Pricing is on request.