1 citations · 2 across the 12 of their papers we have counts for
4 papers · 1 filter
Dream2Real: Zero-Shot 3D Object Rearrangement with Vision-Language Models
Ivan Kapelyukh, Yifei Ren, Ignacio Alzugaray +1
We introduce Dream2Real, a robotics framework which integrates vision-language models (VLMs) trained on 2D data into a 3D object rearrangement pipeline. This is achieved by the rob…
SceneScore: Learning a Cost Function for Object Arrangement
Ivan Kapelyukh, Edward Johns
Arranging objects correctly is a key capability for robots which unlocks a wide range of useful tasks. A prerequisite for creating successful arrangements is the ability to evaluat…
Few-Shot In-Context Imitation Learning via Implicit Graph Alignment
Vitalis Vosylius, Edward Johns
Consider the following problem: given a few demonstrations of a task across a few different objects, how can a robot learn to perform that same task on new, previously unseen objec…
One-Shot Imitation Learning: A Pose Estimation Perspective
Pietro Vitiello, Kamil Dreczkowski, Edward Johns
In this paper, we study imitation learning under the challenging setting of: (1) only a single demonstration, (2) no further data collection, and (3) no prior task or object knowle…