Top 7 Video Annotation Tools & Platforms for 2026
Video annotation is the process of adding labels and metadata to video frames (or time segments) so ML models can learn to detect, track, and understand objects, actions, and events over time.
Video annotation is the process of adding labels and metadata to video frames (or time segments) so ML models can learn to detect, track, and understand objects, actions, and events over time.
Multimodal data is data from multiple modalities, such as text, images, audio, video, and sensors, combined so AI can understand the same event or object with richer context than any single source alone.
Multimodal applications use multimodal AI systems to combine multiple data types within a single model. By integrating diverse data modalities through data fusion, multimodal AI provide understanding of complex, real-world scenarios than unimodal AI.
Multimodal AI processes and combines multimodal data at the same time. Multimodal AI systems gain richer context by aligning visual data, textual data, and other input data and handle complex tasks like image captioning, visual search, and generate human-sounding outputs, than unimodal AI systems.
Multimodal ML annotation platforms comparison guide. Learn key features, AI-assisted labeling, QA, and how to choose the right tool.
Master data augmentation in computer vision with this complete guide. Learn how data augmentation techniques vary and discover how to optimize sample data for your object detection model.
Explore, compare, and contrast the best 10+ data annotation tools for 2026 with our deep-dive article.