Best Video Annotation Tools - Page 2

Innotescus is a collaborative video and image annotation platform built to streamline Computer Vision development processes via seamless data handling, smart annotation tools, and intuitive collaboration features. Additionally, its data visualization tools and cross-functional collaboration features identify data bias early, improve data accuracy, and enable faster, cost-efficient deployment of high performance Artificial Intelligence.

Anolytics provides data annotation service for image, videos & text for machine learning and AI-based computer vision. Anolytics offers a low-cost annotation service for machine learning and artificial intelligence model developments. It is providing the precisely annotated data in the form of text, images and videos using the various annotation techniques while ensuring the accuracy and quality. It is specialized in Image Annotation, Video Annotation and Text Annotation with best accuracy. Anolytics is providing all leading types of data annotation service used as a data training in machine learning and deep learning. It offers Bounding Boxes, Semantic Segmentation, 3D Point Cloud Annotation and 3D Cuboid Annotation for fields like healthcare, autonomous driving or drone falying, retail, security surveillance and agriculture. Anolytics works with scalable solution, available at turnaround time and cost-effective pricing for clients across the globe.

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.

Extend the platform to support annotation for segmentation. The Zastra repository will have algorithms that support segmentation for enabling active learning of datasets. Provide end-to-end ML ops-version control for datasets / experiments and templated pipelines, to deploy the model to standard cloud-based environments and the Edge. Incorporate advances in Bayesian deep learning in the active learning framework. Further, improve the quality of annotations using specialized architectures like Bayesian CNN. Our experts have spent countless hours hand-crafting this breakthrough solution for you. While we’re still actively adding features to the platform, we just couldn’t wait to take you on a test drive! Zastra’s key capabilities include Active-Learning based object classification, object detection, localization, and segmentation. We can do this for images, video, audio, text, and point cloud data.

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.

​Deepen AI offers advanced multi-sensor data labeling and calibration tools and services to accelerate computer vision training for autonomous vehicles, robotics, and more. Their annotation suite supports various key cases, including 2D and 3D bounding boxes, semantic and instance segmentation, polylines, and key points. The platform is AI-powered, featuring pre-labeling capabilities that can automatically label up to 80 common classes, improving productivity by seven times. It also includes machine learning-assisted segmentation, allowing users to segment objects with just a few clicks, and accurate object detection and tracking across frames to avoid duplicate efforts and save time. Deepen AI's calibration suite supports all key sensor types, such as LiDAR, camera, radar, IMU, and vehicle sensors. The tools enable seamless visualization and inspection of multi-sensor data integrity, and calculation of intrinsic and extrinsic calibration parameters in seconds.

Intel® Geti™ software simplifies the process of building computer vision models by enabling fast, accurate data annotation and training. With capabilities like smart annotations, active learning, and task chaining, users can create models for classification, object detection, and anomaly detection without writing additional code. The platform also provides built-in optimizations, hyperparameter tuning, and production-ready models optimized for Intel’s OpenVINO™ toolkit. Designed to support collaboration, Geti™ helps teams streamline model development, from data labeling to model deployment.

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.

When you need transcription, data validation, classification, sentiment analysis, or other related tasks, UHRS can give you what you need. We provide human intelligence to train machine learning models to help you solve some of your most challenging problems. We make it easy for judges to access UHRS anywhere, at any time. All that’s needed is an internet connection, and judges are good to go. Work on tasks like video annotation in just a few minutes. With UHRS, you can classify thousands of images quickly and easily. Train your products and tools with improved image detection, boundary recognition, and more with high quality annotated image data. Classify images, semantic segmentation, object detection. Validating audio to text, conversation, and relevance. Identify sentiment of a tweet, and document classification. Ad hoc data collection tasks, information correction/moderation, and survey.

Klatch Technologies is a global data services provider helping companies and institutions collect, annotate, and process data. We assist Artificial Intelligence companies, research institutions, Machine Learning or Computer Vision projects in data labeling, data collection, content moderation, and other data projects. Our Specialists provide rapid scalability, precise accuracy, swift turnaround time, multilingual capability, and data security at a low-cost. - Data Annotation Services: Image Annotation Video Annotation Search Relevance Text NLP Annotation Text Classification Sentiment Analysis Image Segmentation LIDAR Annotation - Data Collection Services: Healthcare Training Data Chatbot Training Data & all other data collection needs - IT Managed Services: Content Moderation Ecommerce Data Categorization

Systematically manage the end-to-end AI pipeline, from raw data to production. Build custom models that are sensitive to your operations, powering competitive advantage. Build a diverse AI workforce that can easily build and deploy AI, all without a single line of code. Put AI into action anywhere, on the factory floor, in outer space, or anywhere in between. Invest in a proven platform, deployed in some of the most data-sensitive environments. Assisted user flows to walk you through creating your first model. Rather than siloing enterprise data across cloud providers and hardware devices, centralize all media into a single, curated library that is optimized for discoverability.

The training data platform for AI teams. A machine learning model is only as good as its training data. Labelbox is an end-to-end platform to create and manage high-quality training data all in one place, while supporting your production pipeline with powerful APIs. Powerful image labeling tool for image classification, object detection and segmentation. When every pixel matters, you need accurate and intuitive image segmentation tools. Customize the tools to support your specific use case, including instances, custom attributes and much more. Performant video labeling editor for cutting-edge computer vision. Label directly on the video up to 30 FPS with frame level. Additionally, Labelbox provides per frame label feature analytics enabling you to create better models faster. Creating training data for natural language intelligence has never been easier. Label text strings, conversations, paragraphs, and documents with fast & customizable classification.

We Make Data for the World's Most Valuable Companies Innodata solves your toughest data engineering challenges using artificial intelligence and human expertise. Innodata provides the services and solutions you need to harness digital data at scale and drive digital disruption in your industry. We securely and efficiently collect & label your most complex and sensitive data, delivering near-100% accurate ground truth for AI and ML models. Our easy-to-use API ingests your unstructured data (such as contracts and medical records) and generates normalized, schema-compliant structured XML for your downstream applications and analytics. We ensure that your mission-critical databases are accurate and always up-to-date.