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arXiv · 2209.07147

One-Shot Transfer of Affordance Regions? AffCorrs!

Denis Hadjivelichkov·Sicelukwanda Zwane·Marc Peter Deisenroth·Lourdes Agapito·Dimitrios Kanoulas
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Abstract

In this work, we tackle one-shot visual search of object parts. Given a single reference image of an object with annotated affordance regions, we segment semantically corresponding parts within a target scene. We propose AffCorrs, an unsupervised model that combines the properties of pre-trained DINO-ViT's image descriptors and cyclic correspondences. We use AffCorrs to find corresponding affordances both for intra- and inter-class one-shot part segmentation. This task is more difficult than supervised alternatives, but enables future work such as learning affordances via imitation and assisted teleoperation.

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Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas. 2022-09-15. One-Shot Transfer of Affordance Regions? AffCorrs!. https://arxiv.org/abs/2209.07147

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