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arXiv Machine Learning By Seongjin Bien, Carlo Kneissl, Tobias J\"ulg, Frank Fundel, Thomas Ressler-Antal, Florian Walter, Bj\"orn Ommer, Gitta Kutyniok, Wolfram Burgard

FlowTouch: View-Invariant Visuo-Tactile Prediction

Read the original on arXiv Machine Learning →

FlowTouch is a model that predicts tactile sensor outputs from visual data in a view‑invariant manner by leveraging an object’s local 3D mesh to encode rich information while abstracting scene‑dependent details. It integrates scene reconstruction with Flow Matching‑based image generation, enabling it to bridge the sim‑to‑real gap and generalize to new sensor instances. The predicted tactile images can be used for downstream tasks such as grasp stability prediction.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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