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Found 3 papers, 1 papers with code
Any-point Trajectory Modeling for Policy Learning
Learning from demonstration is a powerful method for teaching robots new skills, and having more demonstration data often improves policy learning.
SpawnNet: Learning Generalizable Visuomotor Skills from Pre-trained Networks
In this work, we present a focused study of the generalization capabilities of the pre-trained visual representations at the categorical level.
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data
In this paper, we address this challenge by presenting Sim2Seg, a re-imagining of RCAN that crosses the visual reality gap for off-road autonomous driving, without using any real-world data.
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