3 citations · 5 across the 7 of their papers we have counts for
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cs.RO2024★ 3 cited
EgoMimic: Scaling Imitation Learning via Egocentric Video
Simar Kareer, Dhruv Patel, Ryan Punamiya +5
The scale and diversity of demonstration data required for imitation learning is a significant challenge. We present EgoMimic, a full-stack framework which scales manipulation via…
cs.RO2024★ 1 cited
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations
Julen Urain, Ajay Mandlekar, Yilun Du +5
Learning from Demonstrations, the field that proposes to learn robot behavior models from data, is gaining popularity with the emergence of deep generative models. Although the pro…
cs.CV2024★ 1 cited
Neural Visibility Field for Uncertainty-Driven Active Mapping
Shangjie Xue, Jesse Dill, Pranay Mathur +3
This paper presents Neural Visibility Field (NVF), a novel uncertainty quantification method for Neural Radiance Fields (NeRF) applied to active mapping. Our key insight is that re…