154 citations · 765 across the 31 of their papers we have counts for
34 papers
Crossing the Reality Gap in Tactile-Based Learning
Ya-Yen Tsai, Bidan Huang, Yu Zheng +3
Tactile sensors are believed to be essential in robotic manipulation, and prior works often rely on experts to reason the sensor feedback and design a controller. With the recent a…
Prismer: A Vision-Language Model with Multi-Task Experts
Shikun Liu, Linxi Fan, Edward Johns +3
Recent vision-language models have shown impressive multi-modal generation capabilities. However, typically they require training huge models on massive datasets. As a more scalabl…
Where To Start? Transferring Simple Skills to Complex Environments
Vitalis Vosylius, Edward Johns
Robot learning provides a number of ways to teach robots simple skills, such as grasping. However, these skills are usually trained in open, clutter-free environments, and therefor…
Real-time Mapping of Physical Scene Properties with an Autonomous Robot Experimenter
Iain Haughton, Edgar Sucar, Andre Mouton +2
Neural fields can be trained from scratch to represent the shape and appearance of 3D scenes efficiently. It has also been shown that they can densely map correlated properties suc…
DALL-E-Bot: Introducing Web-Scale Diffusion Models to Robotics
Ivan Kapelyukh, Vitalis Vosylius, Edward Johns
We introduce the first work to explore web-scale diffusion models for robotics. DALL-E-Bot enables a robot to rearrange objects in a scene, by first inferring a text description of…
AGO-Net: Association-Guided 3D Point Cloud Object Detection Network
Liang Du, Xiaoqing Ye, Xiao Tan +5
The human brain can effortlessly recognize and localize objects, whereas current 3D object detection methods based on LiDAR point clouds still report inferior performance for detec…