Action recognition models such as PoseClassificationNet have been around for some time, helping systems identify and classify human actions like walking, waving, or picking up objects. While the concept is well-established, the challenge lies in building a robust computer vision model that can accurately recognize the range of actions across different scenarios that are domain- or use case…
]]>Large-scale, use–case-specific synthetic data has become increasingly important in real-world computer vision and AI workflows. That’s because digital twins are a powerful way to create physics-based virtual replicas of factories, retail spaces, and other assets, enabling precise simulations of real-world environments. NVIDIA Isaac Sim, built on NVIDIA Omniverse, is a fully extensible…
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