activity
20142019
most citedEmbedded real-time stereo estimation via Semi-Global Matching on the GPU

168 citations · 234 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CV201917 cited

Active Learning for Deep Detection Neural Networks

Hamed H. Aghdam, Abel Gonzalez-Garcia, Joost van de Weijer +1

The cost of drawing object bounding boxes (i.e. labeling) for millions of images is prohibitively high. For instance, labeling pedestrians in a regular urban image could take 35 se…

cs.CV20198 cited

Intention Recognition of Pedestrians and Cyclists by 2D Pose Estimation

Zhijie Fang, Antonio M. López

Anticipating the intentions of vulnerable road users (VRUs) such as pedestrians and cyclists is critical for performing safe and comfortable driving maneuvers. This is the case for…

cs.CV20199 cited

Slanted Stixels: A way to represent steep streets

Daniel Hernandez-Juarez, Lukas Schneider, Pau Cebrian +6

This work presents and evaluates a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather re…

cs.CV2016

From Virtual to Real World Visual Perception using Domain Adaptation -- The DPM as Example

Antonio M. Lopez, Jiaolong Xu, Jose L. Gomez +2

Supervised learning tends to produce more accurate classifiers than unsupervised learning in general. This implies that training data is preferred with annotations. When addressing…

cs.CV20165 cited

A Benchmark for Endoluminal Scene Segmentation of Colonoscopy Images

David Vázquez, Jorge Bernal, F. Javier Sánchez +5

Colorectal cancer (CRC) is the third cause of cancer death worldwide. Currently, the standard approach to reduce CRC-related mortality is to perform regular screening in search for…

cs.CV20161 cited

Node-Adapt, Path-Adapt and Tree-Adapt:Model-Transfer Domain Adaptation for Random Forest

Azadeh S. Mozafari, David Vazquez, Mansour Jamzad +1

Random Forest (RF) is a successful paradigm for learning classifiers due to its ability to learn from large feature spaces and seamlessly integrate multi-class classification, as w…