Search Results for author: German Ros

Found 11 papers, 4 papers with code

Objects With Lighting: A Real-World Dataset for Evaluating Reconstruction and Rendering for Object Relighting

1 code implementation17 Jan 2024 Benjamin Ummenhofer, Sanskar Agrawal, Rene Sepulveda, Yixing Lao, Kai Zhang, Tianhang Cheng, Stephan Richter, Shenlong Wang, German Ros

Reconstructing an object from photos and placing it virtually in a new environment goes beyond the standard novel view synthesis task as the appearance of the object has to not only adapt to the novel viewpoint but also to the new lighting conditions and yet evaluations of inverse rendering methods rely on novel view synthesis data or simplistic synthetic datasets for quantitative analysis.

Inverse Rendering Novel View Synthesis

SPIGAN: Privileged Adversarial Learning from Simulation

no code implementations ICLR 2019 Kuan-Hui Lee, German Ros, Jie Li, Adrien Gaidon

Deep Learning for Computer Vision depends mainly on the source of supervision. Photo-realistic simulators can generate large-scale automatically labeled syntheticdata, but introduce a domain gap negatively impacting performance.

Image-to-Image Translation Semantic Segmentation +1

Joint Coarse-And-Fine Reasoning for Deep Optical Flow

no code implementations22 Aug 2018 Victor Vaquero, German Ros, Francesc Moreno-Noguer, Antonio M. Lopez, Alberto Sanfeliu

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 reasoning.

Optical Flow Estimation

Physical Representation-based Predicate Optimization for a Visual Analytics Database

no code implementations11 Jun 2018 Michael R. Anderson, Michael Cafarella, German Ros, Thomas F. Wenisch

Modern extraction techniques are based on deep convolutional neural networks (CNNs) and can classify objects within images with astounding accuracy.

A Dataset To Evaluate The Representations Learned By Video Prediction Models

1 code implementation25 Feb 2018 Ryan Szeto, Simon Stent, German Ros, Jason J. Corso

We present a parameterized synthetic dataset called Moving Symbols to support the objective study of video prediction networks.

Video Prediction

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

no code implementations29 Dec 2016 Antonio M. Lopez, Jiaolong Xu, Jose L. Gomez, David Vazquez, German Ros

However, since the models learned with virtual data must operate in the real world, we still need to perform domain adaptation (DA).

Domain Adaptation

The SYNTHIA Dataset: A Large Collection of Synthetic Images for Semantic Segmentation of Urban Scenes

no code implementations CVPR 2016 German Ros, Laura Sellart, Joanna Materzynska, David Vazquez, Antonio M. Lopez

In order to answer this question we have generated a synthetic collection of diverse urban images, named SYNTHIA, with automatically generated class annotations.

Autonomous Driving Segmentation +1

Training Constrained Deconvolutional Networks for Road Scene Semantic Segmentation

no code implementations6 Apr 2016 German Ros, Simon Stent, Pablo F. Alcantarilla, Tomoki Watanabe

In this work we investigate the problem of road scene semantic segmentation using Deconvolutional Networks (DNs).

Semantic Segmentation

Fast and Robust Fixed-Rank Matrix Recovery

1 code implementation10 Mar 2015 German Ros, Julio Guerrero

We address the problem of efficient sparse fixed-rank (S-FR) matrix decomposition, i. e., splitting a corrupted matrix $M$ into an uncorrupted matrix $L$ of rank $r$ and a sparse matrix of outliers $S$.


Motion Estimation via Robust Decomposition with Constrained Rank

no code implementations22 Oct 2014 German Ros, Jose Alvarez, Julio Guerrero

To this end we propose the Robust Decomposition with Constrained Rank (RD-CR), a proximal gradient based method that enforces the rank constraints inherent to motion estimation.

Motion Estimation Outlier Detection +1

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