616 citations · 967 across the 8 of their papers we have counts for
9 papers
3D hierarchical optimization for Multi-view depth map coding
Marc Maceira, David Varas, Josep-Ramon Morros +2
Depth data has a widespread use since the popularity of high-resolution 3D sensors. In multi-view sequences, depth information is used to supplement the color data of each view. Th…
RVOS: End-to-End Recurrent Network for Video Object Segmentation
Carles Ventura, Miriam Bellver, Andreu Girbau +3
Multiple object video object segmentation is a challenging task, specially for the zero-shot case, when no object mask is given at the initial frame and the model has to find the o…
Recurrent Neural Networks for Semantic Instance Segmentation
Amaia Salvador, Miriam Bellver, Victor Campos +4
We present a recurrent model for semantic instance segmentation that sequentially generates binary masks and their associated class probabilities for every object in an image. Our…
Hierarchical Object Detection with Deep Reinforcement Learning
Miriam Bellver, Xavier Giro-i-Nieto, Ferran Marques +1
We present a method for performing hierarchical object detection in images guided by a deep reinforcement learning agent. The key idea is to focus on those parts of the image that…
Faster R-CNN Features for Instance Search
Amaia Salvador, Xavier Giro-i-Nieto, Ferran Marques +1
Image representations derived from pre-trained Convolutional Neural Networks (CNNs) have become the new state of the art in computer vision tasks such as instance retrieval. This w…
Bags of Local Convolutional Features for Scalable Instance Search
Eva Mohedano, Amaia Salvador, Kevin McGuinness +3
This work proposes a simple instance retrieval pipeline based on encoding the convolutional features of CNN using the bag of words aggregation scheme (BoW). Assigning each local ar…