Best Video Annotation Tools

Video Annotation in Vertex AI enables businesses to label and tag objects, actions, and features in video data, which is crucial for training computer vision models that can analyze and interpret dynamic visual content. Vertex AI offers automated and manual annotation tools that support a wide range of video processing tasks, from object detection to activity recognition. By annotating videos, businesses can train more accurate and effective machine learning models for video analytics. New customers receive $300 in free credits to experiment with video annotation tools and apply them to their own datasets. This capability enables businesses to leverage video data for powerful AI applications in industries such as security, entertainment, and sports analysis.

Ango Hub is a quality-focused, enterprise-ready data annotation platform for AI teams, available on cloud and on-premise. It supports computer vision, medical imaging, NLP, audio, video, and 3D point cloud annotation, powering use cases from autonomous driving and robotics to healthcare AI. Built for AI fine-tuning, RLHF, LLM evaluation, and human-in-the-loop workflows, Ango Hub boosts throughput with automation, model-assisted pre-labeling, and customizable QA while maintaining accuracy. Features include centralized instructions, review pipelines, issue tracking, and consensus across up to 30 annotators. With nearly twenty labeling tools—such as rotated bounding boxes, label relations, nested conditional questions, and table-based labeling—it supports both simple and complex projects. It also enables annotation pipelines for chain-of-thought reasoning and next-gen LLM training and enterprise-grade security with HIPAA compliance, SOC 2 certification, and role-based access controls.

clickworker is globally the largest open crowd sourcing provider. The company has a huge number of services using a "one to many" approach where your company can use many Clickworkers to achieve the outcome you desire. Most frequently, clickworker provides customized data collection, categorization, evaluation, tagging and annotation services to create AI/ML training data for Data Scientists, and also provides SEO texts, product tags, categories and surveys for online businesses and retailers. clickworker serves most industries and applications using the skills of their 4.0M+ Clickworkers. This crowd gathers data through a wide range of micro-tasks, utilizing a sophisticated crowd-sourcing platform and fully featured mobile app.

Clarifai is a leading AI platform for modeling image, video, text and audio data at scale. Our platform combines computer vision, natural language processing and audio recognition as building blocks for developing better, faster and stronger AI. We help our customers create innovative solutions for visual search, content moderation, aerial surveillance, visual inspection, intelligent document analysis, and more. The platform comes with the broadest repository of pre-trained, out-of-the-box AI models built with millions of inputs and context. Our models give you a head start; extending your own custom AI models. Clarifai Community builds upon this and offers 1000s of pre-trained models and workflows from Clarifai and other leading AI builders. Users can build and share models with other community members. Founded in 2013 by Matt Zeiler, Ph.D., Clarifai has been recognized by leading analysts, IDC, Forrester and Gartner, as a leading computer vision AI platform. Visit clarifai.com

Alegion is the data labeling solution for enterprise-grade Machine Learning. We lead the industry in streaming, high-resolution, high-density video annotation, delivering accurately-annotated, model-ready data to train and validate ML models. Alegion provides both the platform and workforce to operate with quality at scale, processing structured and unstructured data including video, image, audio, and text. Our ML powered platform speeds up task completion by as much as 70%, including classless object tracking and single click smart polygon generation. Segmentation options include Keypoint, Bounding Box, Polyline, & Polygon segmentation, for image and video. Semantic Segmentation tools deliver seamless entity boundaries with pixel perfect accuracy. NLP and NER capabilities support text and audio classification and sentiment analysis. The platform is highly configurable to support hybrid use cases. Available via SaaS (Alegion Control), Managed Platform, and Managed Labeling Services.

Keylabs.ai is an advanced image and video annotation platform designed by experts to provide high-performance data annotation, management features, and unique operations management capabilities. With a proven track record of handling large datasets efficiently and accurately, Keylabs.ai is trusted by global technology leaders. It combines innovative technology with a user-centric design to support projects of any type and scale. The platform supports various image and video annotation dataset formats, including semantic segmentation, cuboid 3D point cloud, polygons, key points, lane annotation, and bitmask. Additionally, Keylabs.ai allows seamless integration of client models to meet specific project requirements. The annotation process is enhanced with exclusive post-annotation tools like Edge Smooth and Healer, ensuring greater precision and efficiency. By simplifying image annotation, Keylabs.ai provides AI developers with a high degree of flexibility to optimize workflow.

Keymakr specializes in providing image and video data annotation, data creation, data collection, and data validation services for AI/ML Computer Vision projects. With a strong technological foundation and expertise, Keymakr efficiently manages data across various domains. Keymakr's motto, "Human teaching for machine learning," reflects its commitment to the human-in-the-loop approach. The company maintains an in-house team of over 600 highly skilled annotators. Keymakr's goal is to deliver custom datasets that enhance the accuracy and efficiency of ML systems. Our services: - Image annotation - Video annotation - Data validation - Data creation - Data collection - Generative AI - Custom AI

V7 Darwin is a powerful AI-driven platform for labeling and training data that streamlines the process of annotating images, videos, and other data types. By using AI-assisted tools, V7 Darwin enables faster, more accurate labeling for a variety of use cases such as machine learning model training, object detection, and medical imaging. The platform supports multiple types of annotations, including keypoints, bounding boxes, and segmentation masks. It integrates with various workflows through APIs, SDKs, and custom integrations, making it an ideal solution for businesses seeking high-quality data for their AI projects.

Precise video analysis that recognizes over 20,000 objects, places, and actions in video. Extract rich metadata at the video, shot, or frame level. Create your own custom entity labels with AutoML Video Intelligence. Gain near real-time insights with streaming video annotation and object-based event triggers. Build engaging customer experiences with highlight reels, recommendations, and more. Recognize over 20,000 objects, places, and actions in stored and streaming video. Extract rich metadata at the video, shot, or frame level. Create your own custom entity labels with AutoML Video Intelligence. Search your video catalog the same way you search documents. Extract metadata that can be used to index, organize, and search your video content, as well as control and filter content for what’s most relevant. Gain insights from video in near real-time using streaming video annotation and trigger events based on objects detected.

Label Your Data stands for exceptional data annotation service. With PCI DSS (level 1) and ISO:27001 certifications, and adherence to GDPR, CCPA, and HIPAA, we guarantee your data is handled securely. Our services cover Automotive, Robotics, Fintech, Healthcare, E-commerce, Manufacturing, and Insurance industries. On a mission to co-build an AI-driven economy, we offer customized solutions for both enterprise and R&D projects with 500+ annotators on board. From Computer Vision and NLP annotation to data processing, Label Your Data delivers accurate and secure results to scale your AI projects.

Support various types of annotations on both images and videos. A scalable open-source web annotation tool. Support simple “click and drag” actions and options to add multiple attributes. Feature functions to fit boundaries with Bezier curves and copy shared boundaries. Annotate the area that the driver is currently driving on. Annotate lane marking for vision-based vehicle localization and trajectory planing. Accurate and intuitive four-click method to encapsulate objects of interest. Predict annotations between frames using object tracking and interpolation algorithm for bounding boxes. Annotation predictions for object instances. 2D tracking features extended to 3D.

Mindkosh is the data platform for curating, labeling and validating datasets for your AI projects. Our industry leading data annotation platform combines collaborative features with AI-assisted annotation features to provide a comprehensive suite of tools to label any kind of data, be it Images, videos or 3D pointclouds such as those from Lidar. For images, Mindkosh offers semi-automatic segmentation, pre-labeling for bounding boxes and automatic OCR. For videos, automatic interpolation can reduce massive amounts of manual annotation. And for lidar, 1-click annotation allows you to create cuboids in just 1 click! If you are simply looking to get your data labeled, our high quality data annotation services combined with an easy to use Python SDK and web-based review platform, provide an unmatched experience.

Labellerr is a data annotation platform designed to expedite the preparation of high-quality labeled datasets for AI and machine learning models. It supports various data types, including images, videos, text, PDFs, and audio, catering to diverse annotation needs. The platform offers automated annotation features, such as model-assisted labeling and active learning, to accelerate the labeling process. Additionally, Labellerr provides advanced analytics and smart quality assurance tools to ensure the accuracy and reliability of annotations. For projects requiring specialized knowledge, Labellerr offers expert-in-the-loop services, including access to professionals in fields like healthcare and automotive.

Annotate better with CVAT, the industry-leading data engine for machine learning. Used and trusted by teams at any scale, for data of any scale. CVAT’s blazing-fast, intuitive user interface, was designed by working closely with real-world teams solving real-world problems. From medical to retail to autonomous vehicles, world’s most ambitious AI teams use CVAT as a part of their AI workflow every day. No matter what your input data or expected results are, CVAT is ready. It works great with images, videos, and even 3D. Bounding boxes, polygons, points, skeletons, cuboids, trajectories, and more. Annotate more efficiently with automated interactive algorithms like intelligent scissors, histogram equalization, and more. Gain actionable insights with metrics such as annotator working hours, objects per hour, and more.

The most flexible data annotation tool. Quickly installable. Build custom UIs or use pre-built labeling templates. Configurable layouts and templates adapt to your dataset and workflow. Detect objects on images, boxes, polygons, circular, and key points supported. Partition the image into multiple segments. Use ML models to pre-label and optimize the process. Webhooks, Python SDK, and API allow you to authenticate, create projects, import tasks, manage model predictions, and more. Save time by using predictions to assist your labeling process with ML backend integration. Connect to cloud object storage and label data there directly with S3 and GCP. Prepare and manage your dataset in our Data Manager using advanced filters. Support multiple projects, use cases, and data types in one platform. Start typing in the config, and you can quickly preview the labeling interface. At the bottom of the page, you have live serialization updates of what Label Studio expects as an input.

With Automaton AI’s ADVIT, create, manage and develop high-quality training data and DNN models all in one place. Optimize the data automatically and prepare it for each phase of the computer vision pipeline. Automate the data labeling processes and streamline data pipelines in-house. Manage the structured and unstructured video/image/text datasets in runtime and perform automatic functions that refine your data in preparation for each step of the deep learning pipeline. Upon accurate data labeling and QA, you can train your own model. DNN training needs hyperparameter tuning like batch size, learning, rate, etc. Optimize and transfer learning on trained models to increase accuracy. Post-training, take the model to production. ADVIT also does model versioning. Model development and accuracy parameters can be tracked in run-time. Increase the model accuracy with a pre-trained DNN model for auto-labeling.

Toloka AI offers a data-centric environment that supports fast and scalable AI development across the ML lifecycle with the help of human insight gathered in a responsible & secure way. Toloka is used by organizations in e-commerce, R&D, banking, autonomous vehicles, web services, and more. Toloka relies on a geographically diverse crowd of several million registered users and state-of-the-art technologies for managing data labeling and human-in-the-loop processes. Established in 2014, the company has offices around the world, with headquarters in Lucerne.

We offer the highest quality SLA (>95%), even on the most complex workflows. Our team assists with anything from implementing a robust quality rubric to raising edge cases. As an ethical AI company, we have provided economic opportunities for over 52,000 people from underserved and marginalized communities. ML Assisted annotation created up to 3-4x efficiency improvement for a single class annotation. We quickly adapt to ramp-ups, focus shifts, and edge cases. ISO certified delivery centers, biometric authentication, and user authentication with 2FA ensure a secure work environment. Seamlessly re-prioritize tasks, provide quality feedback, and monitor models in production. We support data of all types. Get more with less. We combine machine learning and humans in the loop to filter data and select images relevant to your use case. Receive sample results based on your initial guidelines. We work with you to identify edge cases and recommend annotation best practices.

Nexdata's AI Data Annotation Platform is a robust solution designed to meet diverse data annotation needs, supporting various types such as 3D point cloud fusion, pixel-level segmentation, speech recognition, speech synthesis, entity relationship, and video segmentation. The platform features a built-in pre-recognition engine that facilitates human-machine interaction and semi-automatic labeling, enhancing labeling efficiency by over 30%. To ensure high-quality data output, it incorporates multi-level quality inspection management functions and supports flexible task distribution workflows, including package-based and item-based assignments. Data security is prioritized through multi-role, multi-level authority management, template watermarking, log auditing, login verification, and API authorization management. The platform offers flexible deployment options, including public cloud deployment for rapid, independent system setup with exclusive computing resources.

Tasq.ai delivers a powerful, no-code platform for building hybrid AI workflows that combine state-of-the-art machine learning with global, decentralized human guidance, ensuring unmatched scalability, control, and precision. It enables teams to configure AI pipelines visually, breaking tasks into micro-workflows that layer automated inference and quality-assured human review. This decoupled orchestration supports diverse use cases across text, computer vision, audio, video, and structured data, with rapid deployment, adaptive sampling, and consensus-based validation built in. Key capabilities include global deployment of highly screened contributors (“Tasqers”) for unbiased, high-accuracy annotations; granular task routing and judgment aggregation to meet confidence thresholds; and seamless integration into ML ops pipelines via drag-and-drop customization.