116 citations · 197 across the 16 of their papers we have counts for
35 papers
HERD: Continuous Human-to-Robot Evolution for Learning from Human Demonstration
Xingyu Liu, Deepak Pathak, Kris M. Kitani
The ability to learn from human demonstration endows robots with the ability to automate various tasks. However, directly learning from human demonstration is challenging since the…
Online No-regret Model-Based Meta RL for Personalized Navigation
Yuda Song, Ye Yuan, Wen Sun +1
The interaction between a vehicle navigation system and the driver of the vehicle can be formulated as a model-based reinforcement learning problem, where the navigation systems (a…
V-MAO: Generative Modeling for Multi-Arm Manipulation of Articulated Objects
Xingyu Liu, Kris M. Kitani
Manipulating articulated objects requires multiple robot arms in general. It is challenging to enable multiple robot arms to collaboratively complete manipulation tasks on articula…
AEI: Actors-Environment Interaction with Adaptive Attention for Temporal Action Proposals Generation
Khoa Vo, Hyekang Joo, Kashu Yamazaki +4
Humans typically perceive the establishment of an action in a video through the interaction between an actor and the surrounding environment. An action only starts when the main ac…
KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation
Xingyu Liu, Shun Iwase, Kris M. Kitani
We present KDFNet, a novel method for 6D object pose estimation from RGB images. To handle occlusion, many recent works have proposed to localize 2D keypoints through pixel-wise vo…
Neighborhood-Aware Neural Architecture Search
Xiaofang Wang, Shengcao Cao, Mengtian Li +1
Existing neural architecture search (NAS) methods often return an architecture with good search performance but generalizes poorly to the test setting. To achieve better generaliza…