112 citations · 318 across the 20 of their papers we have counts for
8 papers · 1 filter
PanoNet3D: Combining Semantic and Geometric Understanding for LiDARPoint Cloud Detection
Xia Chen, Jianren Wang, David Held +1
Visual data in autonomous driving perception, such as camera image and LiDAR point cloud, can be interpreted as a mixture of two aspects: semantic feature and geometric structure.…
PLAS: Latent Action Space for Offline Reinforcement Learning
Wenxuan Zhou, Sujay Bajracharya, David Held
The goal of offline reinforcement learning is to learn a policy from a fixed dataset, without further interactions with the environment. This setting will be an increasingly more i…
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…
SoftGym: Benchmarking Deep Reinforcement Learning for Deformable Object Manipulation
Xingyu Lin, Yufei Wang, Jake Olkin +1
Manipulating deformable objects has long been a challenge in robotics due to its high dimensional state representation and complex dynamics. Recent success in deep reinforcement le…
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…
Uncertainty-aware Self-supervised 3D Data Association
Jianren Wang, Siddharth Ancha, Yi-Ting Chen +1
3D object trackers usually require training on large amounts of annotated data that is expensive and time-consuming to collect. Instead, we propose leveraging vast unlabeled datase…