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Figuring out how handheld objects are positioned is tough in robotics and vision. Using both RGB and depth data helps, but hand blockages and merging data are still tricky. A new study tackles this with a smart deep learning setup. It uses a fresh voting system to blend data and a special module to handle hand interference.
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