197 citations · 305 across the 11 of their papers we have counts for
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cs.CV2016★ 2 cited
Towards Deep Compositional Networks
Domen Tabernik, Matej Kristan, Jeremy L. Wyatt +1
Hierarchical feature learning based on convolutional neural networks (CNN) has recently shown significant potential in various computer vision tasks. While allowing high-quality di…
cs.CV2015★ 2 cited
A Graph Theoretic Approach for Object Shape Representation in Compositional Hierarchies Using a Hybrid Generative-Descriptive Model
Umit Rusen Aktas, Mete Ozay, Ales Leonardis +1
A graph theoretic approach is proposed for object shape representation in a hierarchical compositional architecture called Compositional Hierarchy of Parts (CHOP). In the proposed…