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TVL: A Touch, Vision, and Language Dataset for Multimodal Alignment
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TVL: A Touch, Vision, and Language Dataset for Multimodal Alignment
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TVL: A Touch, Vision, and Language Dataset for Multimodal Alignment TVL A Touch, Vision, and Language Dataset for Multimodal Alignment Max (Letian) Fu 1 Gaurav Datta * 1 Raven Huang * 1 Will Panitch * 1 Jaimyn Drake * 1 Joseph Ortiz 2 Mustafa Mukadam 2 Mike Lambeta 2 Roberto Calandra 3,4 Ken Goldberg 1 1 UC Berkeley 2 Meta AI Research 3 TU Dresden 4 The Centre for Tactile Internet with Human-in-the-Loop (CeTI) Paper Code Dataset Models Citation TL;DR : Multi-modal alignment made easy using GPT-4V pseudolabels. Overview We introduce the Touch-Vision-Language (TVL) dataset, which combines paired tactile and visual observations with both human-annotated and VLM-generated tactile-semantic labels. We then leverage a contrastive learning approach to train a CLIP-aligned tactile encoder and finetune an open-source LLM for a tactile description task. ...
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