Jan 21, 2021 · In this work we tackle the problem of learning rich touch features from cross-modal self-supervision. We evaluate them identifying objects and their properties.
In this paper we propose to learn rich touch representations that enable sample-efficient learning for touch-based perception (i.e. perception in the dark). We ...
Nov 18, 2020 · Several self-supervised learning methods are benchmarked on these datasets, by evaluating few-shot classification on unseen objects and poses.
Sep 12, 2024 · In this work we tackle the problem of learning rich touch features from cross-modal self-supervision. We evaluate them identifying objects and ...
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在这项工作中，我们解决了从交叉模式自我监督中学习丰富的触摸功能的问题。我们评估了它们在几个镜头分类设置中的识别对象及其属性。使用在合成物体和日常 ...
Learning rich touch representations through cross-modal self-supervision. M Zambelli, Y Aytar, F Visin, Y Zhou, R Hadsell. Conference on Robot Learning, 1415 ...
This work uses self-supervision to learn a compact and multimodal representation of sensory inputs, which can then be used to improve the sample efficiency ...
The sense of touch is fundamental in several manipulation tasks, but rarely used in robot manipulation. Self-Supervised Learning Robotics. 13,297.
We introduce a self-supervised representation learning method based on the task of temporal alignment between videos. Ranked #1 on Video Alignment on UPenn ...
Learning Self-Supervised Representations from Vision and Touch for Active Sliding Perception of Deformable Surfaces.