no code implementations • 12 May 2022 • Enric Corona, Gerard Pons-Moll, Guillem Alenyà, Francesc Moreno-Noguer
An exhaustive evaluation demonstrates that our approach is able to capture the underlying body of clothed people with very different body shapes, achieving a significant improvement compared to state-of-the-art.
1 code implementation • 22 Mar 2022 • Georgies Tzelepis, Eren Erdal Aksoy, Júlia Borràs, Guillem Alenyà
Understanding of deformable object manipulations such as textiles is a challenge due to the complexity and high dimensionality of the problem.
1 code implementation • CVPR 2021 • Enric Corona, Albert Pumarola, Guillem Alenyà, Gerard Pons-Moll, Francesc Moreno-Noguer
In this paper we introduce SMPLicit, a novel generative model to jointly represent body pose, shape and clothing geometry.
no code implementations • 14 Dec 2020 • Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, Guillem Alenyà
It consists in recognizing, in an open world, the planning action that best explains a partially observable state transition from a knowledge library of first-order STRIPS actions, which is initially empty.
no code implementations • 30 Sep 2020 • Júlia Borràs, Guillem Alenyà, Carme Torras
Cloth manipulation is very relevant for domestic robotic tasks, but it presents many challenges due to the complexity of representing, recognizing and predicting the behaviour of cloth under manipulation.
2 code implementations • ICLR 2021 • Nicklas Hansen, Rishabh Jangir, Yu Sun, Guillem Alenyà, Pieter Abbeel, Alexei A. Efros, Lerrel Pinto, Xiaolong Wang
A natural solution would be to keep training after deployment in the new environment, but this cannot be done if the new environment offers no reward signal.
no code implementations • 30 Jan 2020 • Alejandro Suárez-Hernández, Javier Segovia-Aguas, Carme Torras, Guillem Alenyà
This knowledge is usually handcrafted and is hard to keep updated, even for system experts.
no code implementations • CVPR 2020 • Enric Corona, Albert Pumarola, Guillem Alenyà, Francesc Moreno-Noguer
The problem of predicting human motion given a sequence of past observations is at the core of many applications in robotics and computer vision.