most citedPixelVAE: A Latent Variable Model for Natural Images

81 citations · 99 across the 8 of their papers we have counts for

collaborators

8 papers

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.LG201681 cited

PixelVAE: A Latent Variable Model for Natural Images

Ishaan Gulrajani, Kundan Kumar, Faruk Ahmed +4

Natural image modeling is a landmark challenge of unsupervised learning. Variational Autoencoders (VAEs) learn a useful latent representation and model global structure well but ha…

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…

cs.CV20162 cited

GPU-based Pedestrian Detection for Autonomous Driving

Victor Campmany, Sergio Silva, Antonio Espinosa +3

We propose a real-time pedestrian detection system for the embedded Nvidia Tegra X1 GPU-CPU hybrid platform. The pipeline is composed by the following state-of-the-art algorithms:…

cs.CV2016

GPU-accelerated real-time stixel computation

Daniel Hernandez-Juarez, Antonio Espinosa, David Vázquez +2

The Stixel World is a medium-level, compact representation of road scenes that abstracts millions of disparity pixels into hundreds or thousands of stixels. The goal of this work i…