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Testing GLOM's ability to infer wholes from ambiguous parts
Laura Culp, Sara Sabour, Geoffrey E. Hinton
The GLOM architecture proposed by Hinton [2021] is a recurrent neural network for parsing an image into a hierarchy of wholes and parts. When a part is ambiguous, GLOM assumes that…
How to represent part-whole hierarchies in a neural network
Geoffrey Hinton
This paper does not describe a working system. Instead, it presents a single idea about representation which allows advances made by several different groups to be combined into an…
Unsupervised part representation by Flow Capsules
Sara Sabour, Andrea Tagliasacchi, Soroosh Yazdani +2
Capsule networks aim to parse images into a hierarchy of objects, parts and relations. While promising, they remain limited by an inability to learn effective low level part descri…
CvxNet: Learnable Convex Decomposition
Boyang Deng, Kyle Genova, Soroosh Yazdani +3
Any solid object can be decomposed into a collection of convex polytopes (in short, convexes). When a small number of convexes are used, such a decomposition can be thought of as a…
Cerberus: A Multi-headed Derenderer
Boyang Deng, Simon Kornblith, Geoffrey Hinton
To generalize to novel visual scenes with new viewpoints and new object poses, a visual system needs representations of the shapes of the parts of an object that are invariant to c…
Dynamic Routing Between Capsules
Sara Sabour, Nicholas Frosst, Geoffrey E Hinton
A capsule is a group of neurons whose activity vector represents the instantiation parameters of a specific type of entity such as an object or an object part. We use the length of…