Riemannian Motion Policies

Nathan D. Ratliff, Jan Issac, Daniel Kappler +2

Training Deep Networks with Synthetic Data: Bridging the Reality Gap by Domain Randomization

Jonathan Tremblay, Aayush Prakash, David Acuna +7

CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification

Zheng Tang, Milind Naphade, Ming-Yu Liu +6

Falling Things: A Synthetic Dataset for 3D Object Detection and Pose Estimation

Jonathan Tremblay, Thang To, Stan Birchfield

Few-Shot Viewpoint Estimation

Hung-Yu Tseng, Shalini De Mello, Jonathan Tremblay +4

The paper introduces a meta-learning framework called MetaView for category-level few-shot viewpoint estimation, enabling accurate pose prediction for new object categories using t…

Region Growing Curriculum Generation for Reinforcement Learning

Artem Molchanov, Karol Hausman, Stan Birchfield +1

Synthetically Trained Neural Networks for Learning Human-Readable Plans from Real-World Demonstrations

Jonathan Tremblay, Thang To, Artem Molchanov +3

Toward Low-Flying Autonomous MAV Trail Navigation using Deep Neural Networks for Environmental Awareness

Nikolai Smolyanskiy, Alexey Kamenev, Jeffrey Smith +1

Robust Learning of Tactile Force Estimation through Robot Interaction

Balakumar Sundaralingam, Alexander Lambert, Ankur Handa +5

Efficient Hierarchical Graph-Based Segmentation of RGBD Videos

Steven Hickson, Stan Birchfield, Irfan Essa +1

Deep Object Pose Estimation for Semantic Robotic Grasping of Household Objects

Jonathan Tremblay, Thang To, Balakumar Sundaralingam +3

An Energy Minimization Approach to 3D Non-Rigid Deformable Surface Estimation Using RGBD Data

Bryan Willimon, Steven Hickson, Ian Walker +1