3 citations · 3 across the 5 of their papers we have counts for
5 papers
HandDGP: Camera-Space Hand Mesh Prediction with Differentiable Global Positioning
Eugene Valassakis, Guillermo Garcia-Hernando
Predicting camera-space hand meshes from single RGB images is crucial for enabling realistic hand interactions in 3D virtual and augmented worlds. Previous work typically divided t…
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…
Learning Eye-in-Hand Camera Calibration from a Single Image
Eugene Valassakis, Kamil Dreczkowski, Edward Johns
Eye-in-hand camera calibration is a fundamental and long-studied problem in robotics. We present a study on using learning-based methods for solving this problem online from a sing…
Coarse-to-Fine for Sim-to-Real: Sub-Millimetre Precision Across Wide Task Spaces
Eugene Valassakis, Norman Di Palo, Edward Johns
In this paper, we study the problem of zero-shot sim-to-real when the task requires both highly precise control with sub-millimetre error tolerance, and wide task space generalisat…
Crossing The Gap: A Deep Dive into Zero-Shot Sim-to-Real Transfer for Dynamics
Eugene Valassakis, Zihan Ding, Edward Johns
Zero-shot sim-to-real transfer of tasks with complex dynamics is a highly challenging and unsolved problem. A number of solutions have been proposed in recent years, but we have fo…