no code implementations • 10 Aug 2019 • Umit Rusen Aktas, Chao Zhao, Marek Kopicki, Ales Leonardis, Jeremy L. Wyatt
First, we present a simulator for generating and testing dexterous grasps.
no code implementations • 13 Jul 2019 • Marek Kopicki, Dominik Belter, Jeremy L. Wyatt
This paper concerns the problem of how to learn to grasp dexterously, so as to be able to then grasp novel objects seen only from a single view-point.
no code implementations • 27 Jun 2019 • Ermano Arruda, Claudio Zito, Mohan Sridharan, Marek Kopicki, Jeremy L. Wyatt
We present a parametric formulation for learning generative models for grasp synthesis from a demonstration.
Robotics
no code implementations • 13 Mar 2019 • Claudio Zito, Valerio Ortenzi, Maxime Adjigble, Marek Kopicki, Rustam Stolkin, Jeremy L. Wyatt
However, this planning approach was tried successfully only on simplified control problems.
no code implementations • 13 Sep 2016 • Domen Tabernik, Matej Kristan, Jeremy L. Wyatt, Aleš Leonardis
We propose a novel analytic model of a basic unit in a layered hierarchical model with both explicit compositional structure and a well-defined discriminative cost function.
no code implementations • ICCV 2015 • Mete Ozay, Umit Rusen Aktas, Jeremy L. Wyatt, Ales Leonardis
We represent the topological relationship between shape components using graphs, which are aggregated to construct a hierarchical graph structure for the shape vocabulary.
1 code implementation • 21 Jan 2015 • Umit Rusen Aktas, Mete Ozay, Ales Leonardis, Jeremy L. Wyatt
A graph theoretic approach is proposed for object shape representation in a hierarchical compositional architecture called Compositional Hierarchy of Parts (CHOP).