Reproduce “Constellation: Learning relational abstractions over objects for compositional imagination” on OpenResearch

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About this paper

James C.R. Whittington, Rishabh Kabra, Loic Matthey, Christopher P. Burgess, Alexander Lerchner

Constellation learns scene arrangements separately from object appearance, allowing layouts to change while retaining the objects. It uses pre-trained MONet object slots and a relational encoder to represent group configuration, then applies symbolic labels such as “circle” to alter relational latents. The authors report five separate relational factors and demonstrate label-conditioned rearrangements on synthetic scenes, not complex real-world scenes.

Summary by alphaXiv.

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