87 citations · 254 across the 9 of their papers we have counts for
9 papers · 1 filter
Human Body Measurement Estimation with Adversarial Augmentation
Nataniel Ruiz, Miriam Bellver, Timo Bolkart +4
We present a Body Measurement network (BMnet) for estimating 3D anthropomorphic measurements of the human body shape from silhouette images. Training of BMnet is performed on data…
SynthRef: Generation of Synthetic Referring Expressions for Object Segmentation
Ioannis Kazakos, Carles Ventura, Miriam Bellver +2
Recent advances in deep learning have brought significant progress in visual grounding tasks such as language-guided video object segmentation. However, collecting large datasets f…
RefVOS: A Closer Look at Referring Expressions for Video Object Segmentation
Miriam Bellver, Carles Ventura, Carina Silberer +3
The task of video object segmentation with referring expressions (language-guided VOS) is to, given a linguistic phrase and a video, generate binary masks for the object to which t…
Mask-guided sample selection for Semi-Supervised Instance Segmentation
Miriam Bellver, Amaia Salvador, Jordi Torres +1
Image segmentation methods are usually trained with pixel-level annotations, which require significant human effort to collect. The most common solution to address this constraint…
Budget-aware Semi-Supervised Semantic and Instance Segmentation
Miriam Bellver, Amaia Salvador, Jordi Torres +1
Methods that move towards less supervised scenarios are key for image segmentation, as dense labels demand significant human intervention. Generally, the annotation burden is mitig…
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…
Detection-aided liver lesion segmentation using deep learning
Miriam Bellver, Kevis-Kokitsi Maninis, Jordi Pont-Tuset +3
A fully automatic technique for segmenting the liver and localizing its unhealthy tissues is a convenient tool in order to diagnose hepatic diseases and assess the response to the…
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…