FeaStNet: Feature-Steered Graph Convolutions for 3D Shape Analysis

CVPR 2018 Nitika VermaEdmond BoyerJakob Verbeek

Convolutional neural networks (CNNs) have massively impacted visual recognition in 2D images, and are now ubiquitous in state-of-the-art approaches. CNNs do not easily extend, however, to data that are not represented by regular grids, such as 3D shape meshes or other graph-structured data, to which traditional local convolution operators do not directly apply... (read more)

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