The text discusses the importance of video annotation in training computer vision models, its differences from image annotation, advantages over image annotations, and various techniques for annotating videos. Video annotation provides more information per unit of data compared to images, allowing for better object detection, segmentation, and pose estimation. The process of annotating videos is more complex than image annotation due to the need to synchronize and track objects across frames. However, with the right tools and techniques, video annotation can be efficient and accurate. The text also highlights the importance of choosing the right tool or service for video annotation, reviewing annotations regularly, using lossless frame compression, and employing interpolation and keyframe identification to speed up the annotation process. Ultimately, understanding the differences between image and video data, as well as the advantages and techniques of video annotation, is crucial for building robust computer vision models.