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arXiv · 2007.06245

Reconstruction Bottlenecks in Object-Centric Generative Models

Martin Engelcke·Oiwi Parker Jones·Ingmar Posner
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Abstract

A range of methods with suitable inductive biases exist to learn interpretable object-centric representations of images without supervision. However, these are largely restricted to visually simple images; robust object discovery in real-world sensory datasets remains elusive. To increase the understanding of such inductive biases, we empirically investigate the role of "reconstruction bottlenecks" for scene decomposition in GENESIS, a recent VAE-based model. We show such bottlenecks determine reconstruction and segmentation quality and critically influence model behaviour.

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Martin Engelcke, Oiwi Parker Jones, Ingmar Posner. 2020-07-13. Reconstruction Bottlenecks in Object-Centric Generative Models. https://arxiv.org/abs/2007.06245

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