Data annotation & labeling blog.

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Maxim Dupont

Maxim Dupont is the founder of LabelVisor, a scientist & software engineer. His hobby of writing tech reviews has become his new way of life. His belief is that together we can achieve the best world.

Multi-Agent Trajectory Prediction in Autonomous Driving

Multi-Agent Trajectory Prediction in Autonomous Driving

Trajectory prediction is one of the fundamental and most complex tasks in the autonomous driving system. It involves calculating the probabilistic distribution of the future positions of all dynamic road users over a specific time horizon. The task of prediction goes beyond simple extrapolation of speed and direction because the

Web3 and Decentralized AI Training Platforms

Web3 and Decentralized AI Training Platforms

The majority of modern machine learning models are controlled by fewer than ten corporations. Such a concentration of power raises serious questions about fairness, innovation, and who truly benefits from the development of artificial intelligence. A new approach is now emerging that challenges this status quo by combining advanced systems

Vision-Based 3D Occupancy Prediction

Vision-Based 3D Occupancy Prediction

Occupancy prediction enables models to forecast which areas of a scene will be occupied, unoccupied, or hazardous in the near future. Unlike traditional object recognition, occupancy prediction allows a system to "look ahead" and understand the dynamics of car, pedestrian, and other road user movement. This is necessary

3D Occupancy Prediction for Autonomous Vehicles: BEV Representation & Voxel Grids

3D Occupancy Prediction for Autonomous Vehicles: BEV Representation & Voxel Grids

The development of autonomous vehicles is intensively stimulating research in the field of robotics and computer vision, where accurate and reliable scene understanding is of particular importance. To ensure safe navigation, autonomous control systems must form a detailed understanding of spatial occupancy, determining which areas of the environment are occupied

Quantum Machine Learning Data Preparation

Quantum Machine Learning Data Preparation

Traditional preprocessing methods, designed for binary logic, do not meet the requirements of superposition and entanglement. Unlike classical systems, where normalization is sufficient, quantum environments require size alignment with qubit geometry. Success lies in rethinking the data architecture from scratch. The solution combines geometric topology with information theory. Key Takeaways

Brain-Computer Interface Data Processing for AI

Brain-Computer Interface Data Processing for AI

Modern BCI systems increasingly rely on a combination of classical analysis methods and deep models, which allows for improving the quality of interpretation and reducing the need for long-term calibration. The development of machine learning algorithms provides the ability to work with large volumes of noisy, dynamic data and extract

Metaverse Content Creation and Annotation

Metaverse Content Creation and Annotation

The Metaverse is not just another VR/AR game or a set of static 3D modeling scenes. It can already be called an interconnected digital world that must be intelligent and interactive. Every element, object, avatar, gesture, and environment must have a clear, machine-readable meaning for this world to function