35 citations · 43 across the 15 of their papers we have counts for
15 papers
Cost-Efficient Multi-Scale Fovea for Semantic-Based Visual Search Attention
João Luzio, Alexandre Bernardino, Plinio Moreno
Semantics are one of the primary sources of top-down preattentive information. Modern deep object detectors excel at extracting such valuable semantic cues from complex visual scen…
Human Scanpath Prediction in Target-Present Visual Search with Semantic-Foveal Bayesian Attention
João Luzio, Alexandre Bernardino, Plinio Moreno
In goal-directed visual tasks, human perception is guided by both top-down and bottom-up cues. At the same time, foveal vision plays a crucial role in directing attention efficient…
Measuring Uncertainty in Shape Completion to Improve Grasp Quality
Nuno Ferreira Duarte, Seyed S. Mohammadi, Plinio Moreno +2
Shape completion networks have been used recently in real-world robotic experiments to complete the missing/hidden information in environments where objects are only observed in on…
Next Best View For Point-Cloud Model Acquisition: Bayesian Approximation and Uncertainty Analysis
Madalena Caldeira, Plinio Moreno
The Next Best View problem is a computer vision problem widely studied in robotics. To solve it, several methodologies have been proposed over the years. Some, more recently, propo…
Semantic-Based Active Perception for Humanoid Visual Tasks with Foveal Sensors
João Luzio, Alexandre Bernardino, Plinio Moreno
The aim of this work is to establish how accurately a recent semantic-based foveal active perception model is able to complete visual tasks that are regularly performed by humans,…
Pose-free object classification from surface contact features in sequences of Robotic grasps
Teresa Alves, Alexandre Bernardino, Plinio Moreno
In this work, we propose two cost efficient methods for object identification, using a multi-fingered robotic hand equipped with proprioceptive sensing. Both methods are trained on…
Learning to search for and detect objects in foveal images using deep learning
Beatriz Paula, Plinio Moreno
The human visual system processes images with varied degrees of resolution, with the fovea, a small portion of the retina, capturing the highest acuity region, which gradually decl…
Force Feedback Control For Dexterous Robotic Hands Using Conditional Postural Synergies
Dimitrios Dimou, Jose Santos-Victor, Plinio Moreno
We present a force feedback controller for a dexterous robotic hand equipped with force sensors on its fingertips. Our controller uses the conditional postural synergies framework…
3DSGrasp: 3D Shape-Completion for Robotic Grasp
Seyed S. Mohammadi, Nuno F. Duarte, Dimitris Dimou +8
Real-world robotic grasping can be done robustly if a complete 3D Point Cloud Data (PCD) of an object is available. However, in practice, PCDs are often incomplete when objects are…
Active Gaze Control for Foveal Scene Exploration
Alexandre M. F. Dias, Luís Simões, Plinio Moreno +1
Active perception and foveal vision are the foundations of the human visual system. While foveal vision reduces the amount of information to process during a gaze fixation, active…
Online Body Schema Adaptation through Cost-Sensitive Active Learning
Gonçalo Cunha, Pedro Vicente, Alexandre Bernardino +2
Humanoid robots have complex bodies and kinematic chains with several Degrees-of-Freedom (DoF) which are difficult to model. Learning the parameters of a kinematic model can be ach…
Action-conditioned Benchmarking of Robotic Video Prediction Models: a Comparative Study
Manuel Serra Nunes, Atabak Dehban, Plinio Moreno +1
A defining characteristic of intelligent systems is the ability to make action decisions based on the anticipated outcomes. Video prediction systems have been demonstrated as a sol…
Action Anticipation for Collaborative Environments: The Impact of Contextual Information and Uncertainty-Based Prediction
Clebeson Canuto, Plinio Moreno, Jorge Samatelo +2
To interact with humans in collaborative environments, machines need to be able to predict (i.e., anticipate) future events, and execute actions in a timely manner. However, the ob…
Applying Domain Randomization to Synthetic Data for Object Category Detection
João Borrego, Atabak Dehban, Rui Figueiredo +3
Recent advances in deep learning-based object detection techniques have revolutionized their applicability in several fields. However, since these methods rely on unwieldy and larg…
High-level Reasoning and Low-level Learning for Grasping: A Probabilistic Logic Pipeline
Laura Antanas, Plinio Moreno, Marion Neumann +4
While grasps must satisfy the grasping stability criteria, good grasps depend on the specific manipulation scenario: the object, its properties and functionalities, as well as the…