anu cvml video annotation tool

Anu CVML Video Annotation Tool provides an end-to-end workflow to create frame-accurate video annotations for computer vision and ML pipelines. It accepts video assets, enforces a defined annotation schema (bounding boxes, polygons, labels, and tracks), and applies labels across frames with options for keyframes and track interpolation. The system stores per-frame data, supports multi-user collaboration, and enforces quality controls to ensure consistency across annotators. Exports align with common CV formats (COCO, VOC, JSON) to integrate with training pipelines. The tool is designed for data science teams, labeling studios, and research labs handling large video datasets. Its differentiators include flexible schema definitions, frame-to-frame interpolation, and robust export adapters to standard schemas, reducing post-processing time and enabling reproducible data labeling workflows.