289 citations · 292 across the 2 of their papers we have counts for
4 papers · 1 filter
SPIGAN: Privileged Adversarial Learning from Simulation
Kuan-Hui Lee, German Ros, Jie Li +1
Deep Learning for Computer Vision depends mainly on the source of supervision.Photo-realistic simulators can generate large-scale automatically labeled syntheticdata, but introduce…
Joint Coarse-And-Fine Reasoning for Deep Optical Flow
Victor Vaquero, German Ros, Francesc Moreno-Noguer +2
We propose a novel representation for dense pixel-wise estimation tasks using CNNs that boosts accuracy and reduces training time, by explicitly exploiting joint coarse-and-fine re…
A Dataset To Evaluate The Representations Learned By Video Prediction Models
Ryan Szeto, Simon Stent, German Ros +1
We present a parameterized synthetic dataset called Moving Symbols to support the objective study of video prediction networks. Using several instantiations of the dataset in which…
Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation
German Ros, Simon Stent, Pablo F. Alcantarilla +1
In this work we investigate the problem of road scene semantic segmentation using Deconvolutional Networks (DNs). Several constraints limit the practical performance of DNs in this…