154 citations · 765 across the 31 of their papers we have counts for
6 papers · 1 filter
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…
Demonstrate Once, Imitate Immediately (DOME): Learning Visual Servoing for One-Shot Imitation Learning
Eugene Valassakis, Georgios Papagiannis, Norman Di Palo +1
We present DOME, a novel method for one-shot imitation learning, where a task can be learned from just a single demonstration and then be deployed immediately, without any further…
Auto-Lambda: Disentangling Dynamic Task Relationships
Shikun Liu, Stephen James, Andrew J. Davison +1
Understanding the structure of multiple related tasks allows for multi-task learning to improve the generalisation ability of one or all of them. However, it usually requires train…