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Found 3 papers, 1 papers with code
Transferring Foundation Models for Generalizable Robotic Manipulation
In this paper, we propose a novel paradigm that effectively leverages language-reasoning segmentation mask generated by internet-scale foundation models, to condition robot manipulation tasks.
AlphaBlock: Embodied Finetuning for Vision-Language Reasoning in Robot Manipulation
We propose a novel framework for learning high-level cognitive capabilities in robot manipulation tasks, such as making a smiley face using building blocks.
CoMAE: Single Model Hybrid Pre-training on Small-Scale RGB-D Datasets
Our CoMAE presents a curriculum learning strategy to unify the two popular self-supervised representation learning algorithms: contrastive learning and masked image modeling.
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