no code implementations • 17 Nov 2023 • Oscar Gil, Alberto Sanfeliu
Human motion trajectory prediction is a very important functionality for human-robot collaboration, specifically in accompanying, guiding, or approaching tasks, but also in social robotics, self-driving vehicles, or security systems.
no code implementations • 14 Dec 2022 • James L. Crowley, Joëlle L Coutaz, Jasmin Grosinger, Javier Vázquez-Salceda, Cecilio Angulo, Alberto Sanfeliu, Luca Iocchi, Anthony G. Cohn
We propose a hierarchical framework for collaborative intelligent systems.
no code implementations • 15 Oct 2022 • Óscar Gil, Alberto Sanfeliu
The navigation of robots in dynamic urban environments, requires elaborated anticipative strategies for the robot to avoid collisions with dynamic objects, like bicycles or pedestrians, and to be human aware.
no code implementations • 27 Aug 2022 • Thomas A. Ciarfuglia, Ionut M. Motoi, Leonardo Saraceni, Mulham Fawakherji, Alberto Sanfeliu, Daniele Nardi
To improve detection and segmentation on the target data, we propose to train the segmentation algorithm with a weak bounding box label, while for tracking we leverage 3D Structure from Motion algorithms to generate new labels from already labelled samples.
no code implementations • 6 Jul 2022 • Oscar Castro, Ely Repiso, Anais Garrell, Alberto Sanfeliu
This paper presents the design of deep learning architectures which allow to classify the social relationship existing between two people who are walking in a side-by-side formation into four possible categories --colleagues, couple, family or friendship.
no code implementations • 15 Jun 2022 • Javier Laplaza, Joan Jaume Oliver, Ramón Romero, Alberto Sanfeliu, Anaís Garrell
In this work, we propose a gesture based language to allow humans to interact with robots using their body in a natural way.
no code implementations • 1 Jun 2022 • J. E. Dominguez-Vidal, Nicolas Rodriguez, Rene Alquezar, Alberto Sanfeliu
In this work we argue that in Human-Robot Collaboration (HRC) tasks, the Perception-Action cycle in HRC tasks can not fully explain the collaborative behaviour of the human and robot and it has to be extended to Perception-Intention-Action cycle, where Intention is a key topic.
no code implementations • 9 May 2022 • Nicolas Ugrinovic, Albert Pumarola, Alberto Sanfeliu, Francesc Moreno-Noguer
We, therefore, propose a coarse-to-fine approach in which we first learn an implicit function that maps the input image to a 3D body shape with a low level of detail, but which correctly fits the underlying human pose, despite its complexity.
Ranked #1 on 3D Reconstruction on 3DPeople
no code implementations • 11 Apr 2022 • Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo, Alberto Sanfeliu, Francesc Moreno-Noguer
For this purpose, we build a residual-like permutation-invariant network that successfully refines potentially corrupted initial 3D poses estimated by an off-the-shelf detector.
3D Multi-Person Pose Estimation (absolute) 3D Multi-Person Pose Estimation (root-relative) +1
1 code implementation • 2 Nov 2021 • Nicolas Ugrinovic, Adria Ruiz, Antonio Agudo, Alberto Sanfeliu, Francesc Moreno-Noguer
We address the problem of multi-person 3D body pose and shape estimation from a single image.
no code implementations • 8 Dec 2019 • Óscar Gil Viyuela, Alberto Sanfeliu
For this reason, this work adds a dense reward function based on SFM and uses the forces in the states like an additional description.
no code implementations • 8 Oct 2019 • Victor Vaquero, Kai Fischer, Francesc Moreno-Noguer, Alberto Sanfeliu, Stefan Milz
Results show that we are able to accurately re-locate over a filtered map, consistently reducing trajectory errors between an average of 35. 1% with respect to a non-filtered map version and of 47. 9% with respect to a standalone map created on the current session.
no code implementations • ICCV 2019 • Albert Pumarola, Jordi Sanchez, Gary P. T. Choi, Alberto Sanfeliu, Francesc Moreno-Noguer
Finally, we design a multi-resolution deep generative network that, given an input image of a dressed human, predicts his/her geometry image (and thus the clothed body shape) in an end-to-end manner.
no code implementations • 28 Mar 2019 • Sergi Caelles, Albert Pumarola, Francesc Moreno-Noguer, Alberto Sanfeliu, Luc van Gool
To achieve this, we concentrate all the heavy computational load to the training phase with two critics that enforce spatial and temporal mask consistency over the last K frames.
no code implementations • CVPR 2018 • Albert Pumarola, Antonio Agudo, Alberto Sanfeliu, Francesc Moreno-Noguer
Given an input image of a person and a desired pose represented by a 2D skeleton, our model renders the image of the same person under the new pose, synthesizing novel views of the parts visible in the input image and hallucinating those that are not seen.
no code implementations • CVPR 2018 • Albert Pumarola, Antonio Agudo, Lorenzo Porzi, Alberto Sanfeliu, Vincent Lepetit, Francesc Moreno-Noguer
We propose a method for predicting the 3D shape of a deformable surface from a single view.
no code implementations • 30 Aug 2018 • Victor Vaquero, Alberto Sanfeliu, Francesc Moreno-Noguer
In this paper we propose a novel approach to estimate dense optical flow from sparse lidar data acquired on an autonomous vehicle.
no code implementations • 28 Aug 2018 • Victor Vaquero, Alberto Sanfeliu, Francesc Moreno-Noguer
Perception technologies in Autonomous Driving are experiencing their golden age due to the advances in Deep Learning.
no code implementations • 23 Aug 2018 • Victor Vaquero, Ivan del Pino, Francesc Moreno-Noguer, Joan Solà, Alberto Sanfeliu, Juan Andrade-Cetto
The system is thoroughly evaluated on the KITTI tracking dataset, and we show the performance boost provided by our CNN-based vehicle detector over a standard geometric approach.
no code implementations • 22 Aug 2018 • Victor Vaquero, German Ros, Francesc Moreno-Noguer, Antonio M. Lopez, Alberto Sanfeliu
We propose a novel representation for dense pixel-wise estimation tasks using CNNs that boosts accuracy and reduces training time, by explicitly exploiting joint coarse-and-fine reasoning.
7 code implementations • ECCV 2018 • Albert Pumarola, Antonio Agudo, Aleix M. Martinez, Alberto Sanfeliu, Francesc Moreno-Noguer
Recent advances in Generative Adversarial Networks (GANs) have shown impressive results for task of facial expression synthesis.
no code implementations • CVPR 2014 • Eduard Trulls, Stavros Tsogkas, Iasonas Kokkinos, Alberto Sanfeliu, Francesc Moreno-Noguer
In this work we propose a technique to combine bottom-up segmentation, coming in the form of SLIC superpixels, with sliding window detectors, such as Deformable Part Models (DPMs).
no code implementations • CVPR 2013 • Eduard Trulls, Iasonas Kokkinos, Alberto Sanfeliu, Francesc Moreno-Noguer
In this work we exploit segmentation to construct appearance descriptors that can robustly deal with occlusion and background changes.