Learning Unsupervised Hierarchical Part Decomposition of 3D Objects from a Single RGB Image

CVPR 2020 Despoina PaschalidouLuc van GoolAndreas Geiger

Humans perceive the 3D world as a set of distinct objects that are characterized by various low-level (geometry, reflectance) and high-level (connectivity, adjacency, symmetry) properties. Recent methods based on convolutional neural networks (CNNs) demonstrated impressive progress in 3D reconstruction, even when using a single 2D image as input... (read more)

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