132 citations · 543 across the 32 of their papers we have counts for
34 papers
Speed Co-Augmentation for Unsupervised Audio-Visual Pre-training
Jiangliu Wang, Jianbo Jiao, Yibing Song +5
This work aims to improve unsupervised audio-visual pre-training. Inspired by the efficacy of data augmentation in visual contrastive learning, we propose a novel speed co-augmenta…
Language-Conditioned Path Planning
Amber Xie, Youngwoon Lee, Pieter Abbeel +1
Contact is at the core of robotic manipulation. At times, it is desired (e.g. manipulation and grasping), and at times, it is harmful (e.g. when avoiding obstacles). However, tradi…
Language Reward Modulation for Pretraining Reinforcement Learning
Ademi Adeniji, Amber Xie, Carmelo Sferrazza +3
Using learned reward functions (LRFs) as a means to solve sparse-reward reinforcement learning (RL) tasks has yielded some steady progress in task-complexity through the years. In…
Multi-View Masked World Models for Visual Robotic Manipulation
Younggyo Seo, Junsu Kim, Stephen James +3
Visual robotic manipulation research and applications often use multiple cameras, or views, to better perceive the world. How else can we utilize the richness of multi-view data? I…
StereoPose: Category-Level 6D Transparent Object Pose Estimation from Stereo Images via Back-View NOCS
Kai Chen, Stephen James, Congying Sui +3
Most existing methods for category-level pose estimation rely on object point clouds. However, when considering transparent objects, depth cameras are usually not able to capture m…
Sim-to-Real via Sim-to-Seg: End-to-end Off-road Autonomous Driving Without Real Data
John So, Amber Xie, Sunggoo Jung +5
Autonomous driving is complex, requiring sophisticated 3D scene understanding, localization, mapping, and control. Rather than explicitly modelling and fusing each of these compone…