43 citations · 107 across the 13 of their papers we have counts for
7 papers · 1 filter
Embarrassingly Simple Model for Early Action Proposal
Marcos Baptista-Ríos, Roberto J. López-Sastre, Franciso Javier Acevedo-Rodríguez +1
Early action proposal consists in generating high quality candidate temporal segments that are likely to contain an action in a video stream, as soon as they happen. Many sophistic…
ISA: Intelligent Speed Adaptation from Appearance
Carlos Herranz-Perdiguero, Roberto J. López-Sastre
In this work we introduce a new problem named Intelligent Speed Adaptation from Appearance (ISA). Technically, the goal of an ISA model is to predict for a given image of a…
In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization
Carlos Herranz-Perdiguero, Carolina Redondo-Cabrera, Roberto J. López-Sastre
While there has been significant progress in solving the problems of image pixel labeling, object detection and scene classification, existing approaches normally address them sepa…
Learning Short-Cut Connections for Object Counting
Daniel Oñoro-Rubio, Mathias Niepert, Roberto J. López-Sastre
Object counting is an important task in computer vision due to its growing demand in applications such as traffic monitoring or surveillance. In this paper, we consider object coun…
Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation
Carolina Redondo-Cabrera, Marcos Baptista-Ríos, Roberto J. López-Sastre
Training a Convolutional Neural Network (CNN) for semantic segmentation typically requires to collect a large amount of accurate pixel-level annotations, a hard and expensive task.…
The challenge of simultaneous object detection and pose estimation: a comparative study
Daniel Oñoro-Rubio, Roberto J. López-Sastre, Carolina Redondo-Cabrera +1
Detecting objects and estimating their pose remains as one of the major challenges of the computer vision research community. There exists a compromise between localizing the objec…
Unsupervised learning from videos using temporal coherency deep networks
Carolina Redondo-Cabrera, Roberto J. López-Sastre
In this work we address the challenging problem of unsupervised learning from videos. Existing methods utilize the spatio-temporal continuity in contiguous video frames as regulari…