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Given a monocular video as input, #HOLD reconstructs 3D hand and object surfaces for every frame without assuming a known object template. Our key insight is that interacting hands and objects provide complementary cues about each other's shape and pose. 1/4

Michael Black

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21,594 次观看 • 2 年前 •via X (Twitter)

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Monocular pose estimation has gotten really good Grab any 2D video and transfer the performance to a 3D character

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As a Product Designer with an educational and professional background in stop motion and frame-to-frame animation, creating these loaders was seamless. I carefully considered the shape of each frame for the desired animation. Here's my process: 👇👇 ◉ ○ ○ ○ - 1/4

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