667 citations · 2.8k across the 127 of their papers we have counts for
8 papers · 2 filters
ALFRED: A Benchmark for Interpreting Grounded Instructions for Everyday Tasks
Mohit Shridhar, Jesse Thomason, Daniel Gordon +5
We present ALFRED (Action Learning From Realistic Environments and Directives), a benchmark for learning a mapping from natural language instructions and egocentric vision to seque…
LatentFusion: End-to-End Differentiable Reconstruction and Rendering for Unseen Object Pose Estimation
Keunhong Park, Arsalan Mousavian, Yu Xiang +1
Current 6D object pose estimation methods usually require a 3D model for each object. These methods also require additional training in order to incorporate new objects. As a resul…
DexPilot: Vision Based Teleoperation of Dexterous Robotic Hand-Arm System
Ankur Handa, Karl Van Wyk, Wei Yang +6
Teleoperation offers the possibility of imparting robotic systems with sophisticated reasoning skills, intuition, and creativity to perform tasks. However, current teleoperation so…
Part Segmentation for Highly Accurate Deformable Tracking in Occlusions via Fully Convolutional Neural Networks
Weilin Wan, Aaron Walsman, Dieter Fox
Successfully tracking the human body is an important perceptual challenge for robots that must work around people. Existing methods fall into two broad categories: geometric tracki…
The Best of Both Modes: Separately Leveraging RGB and Depth for Unseen Object Instance Segmentation
Christopher Xie, Yu Xiang, Arsalan Mousavian +1
In order to function in unstructured environments, robots need the ability to recognize unseen novel objects. We take a step in this direction by tackling the problem of segmenting…
PoseRBPF: A Rao-Blackwellized Particle Filter for 6D Object Pose Tracking
Xinke Deng, Arsalan Mousavian, Yu Xiang +3
Tracking 6D poses of objects from videos provides rich information to a robot in performing different tasks such as manipulation and navigation. In this work, we formulate the 6D o…