The process of adding metadata, tags, or labels to various objects, actions, or events in a video is known as video annotation. Human annotators can perform this manually, but with AI, a significant portion of the process may be automated. AI algorithms use computer vision to examine and comprehend the contents of the video frame by frame and then recognize and classify objects, actions, or events based on their visual elements.
Let’s look at some of the best AI video annotation tools.
Keylabs is a platform that combines cutting-edge, user-friendly, performance-oriented annotation tools with integrated machine learning and operation management features. It has a tool for AI-powered video annotation. It can create tags, provide descriptions, and identify key moments in videos. Users may create, schedule, and manage tasks for each team member and collaborate on projects.
Labelbox is a free AI video annotation tool. It automates the annotation process using deep learning models, which helps to cut down on the time and labor needed to annotate videos. It provides customers total visibility and control over data labeling operations with internal labeling teams and external labeling service providers through access to a full range of labeling, collaboration, and quality tools.
Dataloop is a complete AI video annotation tool that provides various annotation functions, such as object detection, image segmentation, and text annotation. It offers features like FRAME-BY-FRAME NAVIGATION, LIVE CLASS SWITCHING, and IDS & PARENTING. Teams working on big projects should utilize this application because it is simple to use and has real-time collaboration features.
SuperAnnotate claims to be the foundation of the data labeling workflow. Users can annotate any sort of data, including images, video, text, LiDAR, audio, and more, with its state-of-the-art annotation tool. It enables users to annotate, highlight, and visualize videos. It allows them to annotate movies from a wide range of sources, including Facebook, Vimeo, and YouTube.
Supervisely is an all-in-one video annotation solution. It allows users to deal with their video clips without first cutting them into images, unlike many other labeling tools. It makes use of both natural language processing and deep learning methods. It contains a multi-track timeline, integrated object tracking, and segment tagging capabilities, and it can be used in the browser.
VGG Image Annotator (VIA) is a straightforward and independent manual annotation tool for images, audio, and video. The VIA program is a small, standalone, offline software package that operates in a web browser and doesn’t need to be installed or set up. The application has an easy-to-use UI that is simple and intuitive, making it suitable for beginners.
VideoAnt is a web-based video annotation application for mobile and desktop platforms. Users can use VideoAnt to add annotations, or comments, to web-hosted videos. It provides a platform for secure sharing. Users can share their annotated documents with other team members in a variety of formats by exporting them. Moreover, users can embed their annotated videos wherever HTML is permitted, such as on a personal website or learning management system.
Flixier is a free video annotation platform. It makes it simple for users to annotate videos right from their browsers. With the use of Flixier’s video annotation tool, they may annotate their films with drawings, text, motion titles, photos, shapes, and other elements. It is compatible with all popular video file types, such as mp4, avi, mkv, etc.
The video annotation tool from Deepen AI is an excellent tool for annotating a video to create quality training data. Deepen AI supports many cases, including bounding boxes, polylines, semantic segmentation, and scenario labeling. By confirming the labeled data quality, it guarantees the highest standard. Additionally, it offers a single platform for assigning and managing various team members.
Computer Vision Annotation Tool (CVAT)
CVAT is an open-source, web-based tool to annotate photos, videos, and other types of data for computer vision tasks like object detection, image segmentation, and image classification. CVAT offers a user-friendly interface for annotating pictures and videos, allowing multiple users to collaborate on the same project at once. Moreover, it provides robust annotation tools that let users annotate objects in various shapes.
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The process of adding metadata, tags, or labels to various objects, actions, or events in a video is known as video annotation. Human annotators can perform this manually, but with AI, a significant portion of the process may be automated. AI algorithms use computer vision to examine and comprehend the contents of the video frame
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