research
∙
07/28/2023
RT-2: Vision-Language-Action Models Transfer Web Knowledge to Robotic Control
We study how vision-language models trained on Internet-scale data can b...
share
research
∙
05/05/2023
Deep RL at Scale: Sorting Waste in Office Buildings with a Fleet of Mobile Manipulators
We describe a system for deep reinforcement learning of robotic manipula...
research
∙
03/02/2023
Open-World Object Manipulation using Pre-trained Vision-Language Models
For robots to follow instructions from people, they must be able to conn...
research
∙
10/15/2022
PI-QT-Opt: Predictive Information Improves Multi-Task Robotic Reinforcement Learning at Scale
The predictive information, the mutual information between the past and ...
research
∙
06/07/2019
Watch, Try, Learn: Meta-Learning from Demonstrations and Reward
Imitation learning allows agents to learn complex behaviors from demonst...
research
∙
03/25/2019
Generalized Feedback Loop for Joint Hand-Object Pose Estimation
We propose an approach to estimating the 3D pose of a hand, possibly han...
research
∙
12/18/2018
Sim-to-Real via Sim-to-Sim: Data-efficient Robotic Grasping via Randomized-to-Canonical Adaptation Networks
Real world data, especially in the domain of robotics, is notoriously co...
research
∙
10/29/2017
On Pre-Trained Image Features and Synthetic Images for Deep Learning
Deep Learning methods usually require huge amounts of training data to p...
research
∙
09/22/2017
Using Simulation and Domain Adaptation to Improve Efficiency of Deep Robotic Grasping
Instrumenting and collecting annotated visual grasping datasets to train...
research
∙
09/30/2016
Training a Feedback Loop for Hand Pose Estimation
We propose an entirely data-driven approach to estimating the 3D pose of...
research
∙
02/24/2015
Hands Deep in Deep Learning for Hand Pose Estimation
We introduce and evaluate several architectures for Convolutional Neural...
research
∙
02/20/2015
