Search Results for author: Carolina Redondo-Cabrera

Found 4 papers, 2 papers with code

In pixels we trust: From Pixel Labeling to Object Localization and Scene Categorization

no code implementations19 Jul 2018 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 separately.

object-detection Object Detection +4

Learning to Exploit the Prior Network Knowledge for Weakly-Supervised Semantic Segmentation

1 code implementation13 Apr 2018 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.

Weakly supervised Semantic Segmentation Weakly-Supervised Semantic Segmentation

Unsupervised learning from videos using temporal coherency deep networks

1 code implementation24 Jan 2018 Carolina Redondo-Cabrera, Roberto J. López-Sastre

We here propose two Siamese architectures for Convolutional Neural Networks, and their corresponding novel loss functions, to learn from unlabeled videos, which jointly exploit the local temporal coherence between contiguous frames, and a global discriminative margin used to separate representations of different videos.

Cannot find the paper you are looking for? You can Submit a new open access paper.