アフォーダンス領域のワンショット転移：AffCorrs！
One-Shot Transfer of Affordance Regions? AffCorrs!
参照画像のアフォーダンス領域を手がかりに、対象シーン内の意味的に対応する部位をワンショットでセグメンテーションする教師なしモデルAffCorrsを提案。
著者: Denis Hadjivelichkov, Sicelukwanda Zwane, Marc Peter Deisenroth, Lourdes Agapito, Dimitrios Kanoulas
分類: cs.CV, cs.RO
原文アブストラクト
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.
