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In this work, we introduce general purpose touch representations for the increasingly accessible class of vision-based tactile sensors.
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Learn from incomplete tactile data: Tactile representation learning with masked autoencoders
G. Cao, J. Jiang, D. Bollegala, and S. Luo · 2023
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Dexterity from touch: Self-supervised pre-training of tactile representations with robotic play
I. Guzey, B. Evans, S. Chintala, and L. Pinto · 2023
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Tactile gym 2.0: Sim-to-real deep reinforcement learning for comparing low-cost high-resolution robot touch
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Masked autoencoders are scalable vision learners
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GelSlim 3.0: High-resolution measurement of shape, force and slip in a compact tactile-sensing finger
I. H. Taylor, S. Dong, and A. Rodriguez · 2022
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The objectfolder benchmark: Multisensory learning with neural and real objects
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Self-supervised visuo-tactile pretraining to locate and follow garment features
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