8 citations · 9 across the 2 of their papers we have counts for
5 papers
IFOR: Iterative Flow Minimization for Robotic Object Rearrangement
Ankit Goyal, Arsalan Mousavian, Chris Paxton +4
Accurate object rearrangement from vision is a crucial problem for a wide variety of real-world robotics applications in unstructured environments. We propose IFOR, Iterative Flow…
ZePHyR: Zero-shot Pose Hypothesis Rating
Brian Okorn, Qiao Gu, Martial Hebert +1
Pose estimation is a basic module in many robot manipulation pipelines. Estimating the pose of objects in the environment can be useful for grasping, motion planning, or manipulati…
ROLL: Visual Self-Supervised Reinforcement Learning with Object Reasoning
Yufei Wang, Gautham Narayan Narasimhan, Xingyu Lin +2
Current image-based reinforcement learning (RL) algorithms typically operate on the whole image without performing object-level reasoning. This leads to inefficient goal sampling a…
Robust Instance Tracking via Uncertainty Flow
Jianing Qian, Junyu Nan, Siddharth Ancha +2
Current state-of-the-art trackers often fail due to distractorsand large object appearance changes. In this work, we explore the use ofdense optical flow to improve tracking robust…
Just Go with the Flow: Self-Supervised Scene Flow Estimation
Himangi Mittal, Brian Okorn, David Held
When interacting with highly dynamic environments, scene flow allows autonomous systems to reason about the non-rigid motion of multiple independent objects. This is of particular…