Browsing by Author "Moreno-Noguer, Francesc"
Now showing items 21-40 of 165
-
Body size and depth disambiguation in multi-person reconstruction from single images
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessWe address the problem of multi-person 3D body pose and shape estimation from a single image. While this problem can be addressed by applying single-person approaches multiple times for the same scene, recent works have ... -
Boosted Random ferns for object detection
(2018-02-01)
Article
Open AccessIn this paper we introduce the Boosted Random Ferns (BRFs) to rapidly build discriminative classifiers for learning and detecting object categories. At the core of our approach we use standard random ferns, but we introduce ... -
Breakingnews: article annotation by image and text processing
(Institute of Electrical and Electronics Engineers (IEEE), 2018-05-01)
Article
Open AccessBuilding upon recent Deep Neural Network architectures, current approaches lying in the intersection of Computer Vision and Natural Language Processing have achieved unprecedented breakthroughs in tasks like automatic ... -
C-Flow: conditional generative flow models for images and 3D point clouds
(Institute of Electrical and Electronics Engineers (IEEE), 2020)
Conference report
Open AccessFlow-based generative models have highly desirable properties like exact log-likelihood evaluation and exact latent-variable inference, however they are still in their infancy and have not received as much attention as ... -
Challenge 4: Intelligent robotics
(Consejo Superior de Investigaciones Científicas (CSIC), 2021)
Part of book or chapter of book
Restricted access - publisher's policyIntelligent robotics are called to be the next revolution by providing AI with the capability of interacting with the physical world. Robots are overpassing their cages in the industry to become intelligent machines that ... -
Characterization of textile grasping experiments
(2012)
Conference report
Open AccessGrasping highly deformable objects, like textiles, is an emerging area of research that involves both percep- tion and manipulation abilities. As new techniques appear, it becomes essential to design strategies to compare ... -
Combining geometric and appearance priors for robust homography estimation
(Springer, 2010)
Conference report
Restricted access - publisher's policyAbstract. The homography between pairs of images are typically computed from the correspondence of keypoints, which are established by using image descriptors. When these descriptors are not reliable, either because of ... -
Combining geometric, textual and visual features for predicting prepositions in image descriptions
(2016)
Conference report
Open AccessWe investigate the role that geometric, textual and visual features play in the task of predicting a preposition that links two visual entities depicted in an image. The task is an important part of the subsequent process ... -
Combining local-physical and global-statistical models for sequential deformable shape from motion
(2017-04-01)
Article
Open AccessIn this paper, we simultaneously estimate camera pose and non-rigid 3D shape from a monocular video, using a sequential solution that combines local and global representations. We model the object as an ensemble of particles, ... -
Context and intention for 3D human motion prediction: experimentation and user study in handover tasks
(Institute of Electrical and Electronics Engineers (IEEE), 2022)
Conference report
Open AccessIn this work we present a novel attention deep learning model that uses context and human intention for 3D human body motion prediction in handover human-robot tasks. This model uses a multi-head attention architecture ... -
Context attention: human motion prediction using context information and deep learning attention models
(Springer, 2022)
Conference lecture
Open AccessThis work proposes a human motion prediction model for handover operations. The model uses a multi-headed attention architecture to process the human skeleton data together with contextual data from the operation. This ... -
Context-aware human motion prediction
(2020)
Conference lecture
Open AccessThe problem of predicting human motion given a sequence of past observations is at the core of many applications in robotics and computer vision. Current state-of-the-art formulates this problem as a sequence-to-sequence ... -
D-NeRF: neural radiance fields for dynamic scenes
(Institute of Electrical and Electronics Engineers (IEEE), 2021)
Conference report
Open AccessNeural rendering techniques combining machine learning with geometric reasoning have arisen as one of the most promising approaches for synthesizing novel views of a scene from a sparse set of images. Among these, stands ... -
DaLI: deformation and light invariant descriptor
(2015-11-01)
Article
Open AccessRecent advances in 3D shape analysis and recognition have shown that heat diffusion theory can be effectively used to describe local features of deforming and scaling surfaces. In this paper, we show how this description ... -
Database for 3D human pose estimation from single depth images
(2016)
Research report
Open AccessThis work is part of the project I--DRESS (Assistive interactive robotic system for support in dressing). The specific objective is the detection of human body postures and the tracking of their movements. To this end, ... -
Deconvolutional networks for point-cloud vehicle detection and tracking in driving scenarios
(IEEE Press, 2017)
Conference report
Open AccessVehicle detection and tracking is a core ingredient for developing autonomous driving applications in urban scenarios. Recent image-based Deep Learning (DL) techniques are obtaining breakthrough results in these perceptive ... -
Deep lidar CNN to understand the dynamics of moving vehicles
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessPerception technologies in Autonomous Driving are experiencing their golden age due to the advances in Deep Learning. Yet, most of these systems rely on the semantically rich information of RGB images. Deep Learning solutions ... -
Deformable motion 3D reconstruction by union of regularized subspaces
(Institute of Electrical and Electronics Engineers (IEEE), 2018)
Conference report
Open AccessThis paper presents an approach to jointly retrieve camera pose, time-varying 3D shape, and automatic clustering based on motion primitives, from incomplete 2D trajectories in a monocular video. We introduce the concept ... -
Deformation and illumination invariant feature point descriptor
(2011)
Conference report
Open AccessRecent advances in 3D shape recognition have shown that kernels based on diffusion geometry can be effectively used to describe local features of deforming surfaces. In this paper, we introduce a new framework that ... -
Dense segmentation-aware descriptors
(Springer, 2016)
Part of book or chapter of book
Restricted access - publisher's policyDense descriptors are becoming increasingly popular in a host of tasks, such as dense image correspondence, bag-of-words image classification, and label transfer. However, the extraction of descriptors on generic image ...
