Inductive Biases for Object-Centric Representations of Complex Textures

• URL: http://arxiv.org/abs/2204.08479v1
• Date: Mon, 18 Apr 2022 17:34:37 GMT
• Title: Inductive Biases for Object-Centric Representations of Complex Textures
• Authors: Samuele Papa, Ole Winther, Andrea Dittadi
• Abstract summary: We use neural style transfer to generate datasets where objects have complex textures while still retaining ground-truth annotations. We find that, when a model effectively balances the importance of shape and appearance in the training objective, it can achieve better separation of the objects and learn more useful object representations.
• Score: 13.045904773946367
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Understanding which inductive biases could be useful for the unsupervised learning of object-centric representations of natural scenes is challenging. Here, we use neural style transfer to generate datasets where objects have complex textures while still retaining ground-truth annotations. We find that, when a model effectively balances the importance of shape and appearance in the training objective, it can achieve better separation of the objects and learn more useful object representations.

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