3D-PRNN: Generating Shape Primitives with Recurrent Neural Networks

ICCV 2017 Chuhang ZouErsin YumerJimei YangDuygu CeylanDerek Hoiem

The success of various applications including robotics, digital content creation, and visualization demand a structured and abstract representation of the 3D world from limited sensor data. Inspired by the nature of human perception of 3D shapes as a collection of simple parts, we explore such an abstract shape representation based on primitives... (read more)

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