A visual-tactile fusion network that conditions cross-modal attention on SimCLR contrastive embeddings improves material classification and grasp-success prediction in real-robot datasets.
The objectfolder benchmark: Multisensory learning with neural and real objects,
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ConViTac: Aligning Visual-Tactile Fusion with Contrastive Representations
A visual-tactile fusion network that conditions cross-modal attention on SimCLR contrastive embeddings improves material classification and grasp-success prediction in real-robot datasets.