| Records |
Author  |
Daniel Hernandez; Alejandro Chacon; Antonio Espinosa; David Vazquez; Juan Carlos Moure; Antonio Lopez |
| Title |
Stereo Matching using SGM on the GPU |
Type |
Report |
| Year |
2016 |
Publication |
Programming and Tuning Massively Parallel Systems |
Abbreviated Journal |
PUMPS |
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
CUDA; Stereo; Autonomous Vehicle |
| Abstract |
Dense, robust and real-time computation of depth information from stereo-camera systems is a computationally demanding requirement for robotics, advanced driver assistance systems (ADAS) and autonomous vehicles. Semi-Global Matching (SGM) is a widely used algorithm that propagates consistency constraints along several paths across the image. This work presents a real-time system producing reliable disparity estimation results on the new embedded energy efficient GPU devices. Our design runs on a Tegra X1 at 42 frames per second (fps) for an image size of 640x480, 128 disparity levels, and using 4 path directions for the SGM method. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
PUMPS |
| Notes |
ADAS; 600.085; 600.087; 600.076 |
Approved |
no |
| Call Number |
ADAS @ adas @ HCE2016b |
Serial |
2776 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan C. Moure |
| Title |
3D Perception With Slanted Stixels on GPU |
Type |
Journal Article |
| Year |
2021 |
Publication |
IEEE Transactions on Parallel and Distributed Systems |
Abbreviated Journal |
TPDS |
| Volume |
32 |
Issue |
10 |
Pages |
2434-2447 |
| Keywords |
Daniel Hernandez-Juarez; Antonio Espinosa; David Vazquez; Antonio M. Lopez; Juan C. Moure |
| Abstract |
This article presents a GPU-accelerated software design of the recently proposed model of Slanted Stixels, which represents the geometric and semantic information of a scene in a compact and accurate way. We reformulate the measurement depth model to reduce the computational complexity of the algorithm, relying on the confidence of the depth estimation and the identification of invalid values to handle outliers. The proposed massively parallel scheme and data layout for the irregular computation pattern that corresponds to a Dynamic Programming paradigm is described and carefully analyzed in performance terms. Performance is shown to scale gracefully on current generation embedded GPUs. We assess the proposed methods in terms of semantic and geometric accuracy as well as run-time performance on three publicly available benchmark datasets. Our approach achieves real-time performance with high accuracy for 2048 × 1024 image sizes and 4 × 4 Stixel resolution on the low-power embedded GPU of an NVIDIA Tegra Xavier. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS; 600.124; 600.118 |
Approved |
no |
| Call Number |
Admin @ si @ HEV2021 |
Serial |
3561 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure |
| Title |
GPU-accelerated real-time stixel computation |
Type |
Conference Article |
| Year |
2017 |
Publication |
IEEE Winter Conference on Applications of Computer Vision |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
1054-1062 |
| Keywords |
Autonomous Driving; GPU; Stixel |
| Abstract |
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 is to implement and evaluate a complete multi-stixel estimation pipeline on an embedded, energyefficient, GPU-accelerated device. This work presents a full GPU-accelerated implementation of stixel estimation that produces reliable results at 26 frames per second (real-time) on the Tegra X1 for disparity images of 1024×440 pixels and stixel widths of 5 pixels, and achieves more than 400 frames per second on a high-end Titan X GPU card. |
| Address |
Santa Rosa; CA; USA; March 2017 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
WACV |
| Notes |
ADAS; 600.118 |
Approved |
no |
| Call Number |
ADAS @ adas @ HEV2017b |
Serial |
2812 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Antonio Espinosa; David Vazquez; Antonio Lopez; Juan Carlos Moure |
| Title |
Embedded Real-time Stixel Computation |
Type |
Conference Article |
| Year |
2017 |
Publication |
GPU Technology Conference |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
GPU; CUDA; Stixels; Autonomous Driving |
| Abstract |
|
| Address |
Silicon Valley; USA; May 2017 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
GTC |
| Notes |
ADAS; 600.118 |
Approved |
no |
| Call Number |
ADAS @ adas @ HEV2017a |
Serial |
2879 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Juan Carlos Moure; Toni Espinosa; Alejandro Chacon; David Vazquez; Antonio Lopez |
| Title |
Real-time 3D Reconstruction for Autonomous Driving via Semi-Global Matching |
Type |
Conference Article |
| Year |
2016 |
Publication |
GPU Technology Conference |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Stereo; Autonomous Driving; GPU; 3d reconstruction |
| Abstract |
Robust and dense computation of depth information from stereo-camera systems is a computationally demanding requirement for real-time autonomous driving. Semi-Global Matching (SGM) [1] approximates heavy-computation global algorithms results but with lower computational complexity, therefore it is a good candidate for a real-time implementation. SGM minimizes energy along several 1D paths across the image. The aim of this work is to provide a real-time system producing reliable results on energy-efficient hardware. Our design runs on a NVIDIA Titan X GPU at 104.62 FPS and on a NVIDIA Drive PX at 6.7 FPS, promising for real-time platforms |
| Address |
Silicon Valley; San Francisco; USA; April 2016 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
GTC |
| Notes |
ADAS; 600.085; 600.082; 600.076 |
Approved |
no |
| Call Number |
ADAS @ adas @ HME2016 |
Serial |
2738 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Lukas Schneider; Antonio Espinosa; David Vazquez; Antonio Lopez; Uwe Franke; Marc Pollefeys; Juan C. Moure |
| Title |
Slanted Stixels: Representing San Francisco's Steepest Streets} |
Type |
Conference Article |
| Year |
2017 |
Publication |
28th British Machine Vision Conference |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
In this work we present a novel compact scene representation based on Stixels that infers geometric and semantic information. Our approach overcomes the previous rather restrictive geometric assumptions for Stixels by introducing a novel depth model to account for non-flat roads and slanted objects. Both semantic and depth cues are used jointly to infer the scene representation in a sound global energy minimization formulation. Furthermore, a novel approximation scheme is introduced that uses an extremely efficient over-segmentation. In doing so, the computational complexity of the Stixel inference algorithm is reduced significantly, achieving real-time computation capabilities with only a slight drop in accuracy. We evaluate the proposed approach in terms of semantic and geometric accuracy as well as run-time on four publicly available benchmark datasets. Our approach maintains accuracy on flat road scene datasets while improving substantially on a novel non-flat road dataset. |
| Address |
London; uk; September 2017 |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
BMVC |
| Notes |
ADAS; 600.118 |
Approved |
no |
| Call Number |
ADAS @ adas @ HSE2017a |
Serial |
2945 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Hernandez; Lukas Schneider; P. Cebrian; A. Espinosa; David Vazquez; Antonio Lopez; Uwe Franke; Marc Pollefeys; Juan Carlos Moure |
| Title |
Slanted Stixels: A way to represent steep streets |
Type |
Journal Article |
| Year |
2019 |
Publication |
International Journal of Computer Vision |
Abbreviated Journal |
IJCV |
| Volume |
127 |
Issue |
|
Pages |
1643–1658 |
| Keywords |
|
| Abstract |
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 restrictive geometric assumptions for Stixels by introducing a novel depth model to account for non-flat roads and slanted objects. Both semantic and depth cues are used jointly to infer the scene representation in a sound global energy minimization formulation. Furthermore, a novel approximation scheme is introduced in order to significantly reduce the computational complexity of the Stixel algorithm, and then achieve real-time computation capabilities. The idea is to first perform an over-segmentation of the image, discarding the unlikely Stixel cuts, and apply the algorithm only on the remaining Stixel cuts. This work presents a novel over-segmentation strategy based on a fully convolutional network, which outperforms an approach based on using local extrema of the disparity map. We evaluate the proposed methods in terms of semantic and geometric accuracy as well as run-time on four publicly available benchmark datasets. Our approach maintains accuracy on flat road scene datasets while improving substantially on a novel non-flat road dataset. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS; 600.118; 600.124 |
Approved |
no |
| Call Number |
Admin @ si @ HSC2019 |
Serial |
3304 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Marczak; Grzegorz Rypesc; Sebastian Cygert; Tomasz Trzcinski; Bartłomiej Twardowski |
| Title |
Generalized Continual Category Discovery |
Type |
Miscellaneous |
| Year |
2023 |
Publication |
arxiv |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
Most of Continual Learning (CL) methods push the limit of supervised learning settings, where an agent is expected to learn new labeled tasks and not forget previous knowledge. However, these settings are not well aligned with real-life scenarios, where a learning agent has access to a vast amount of unlabeled data encompassing both novel (entirely unlabeled) classes and examples from known classes. Drawing inspiration from Generalized Category Discovery (GCD), we introduce a novel framework that relaxes this assumption. Precisely, in any task, we allow for the existence of novel and known classes, and one must use continual version of unsupervised learning methods to discover them. We call this setting Generalized Continual Category Discovery (GCCD). It unifies CL and GCD, bridging the gap between synthetic benchmarks and real-life scenarios. With a series of experiments, we present that existing methods fail to accumulate knowledge from subsequent tasks in which unlabeled samples of novel classes are present. In light of these limitations, we propose a method that incorporates both supervised and unsupervised signals and mitigates the forgetting through the use of centroid adaptation. Our method surpasses strong CL methods adopted for GCD techniques and presents a superior representation learning performance. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
LAMP |
Approved |
no |
| Call Number |
Admin @ si @ MRC2023 |
Serial |
3985 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Marczak; Sebastian Cygert; Tomasz Trzcinski; Bartlomiej Twardowski |
| Title |
Revisiting Supervision for Continual Representation Learning |
Type |
Miscellaneous |
| Year |
2023 |
Publication |
Arxiv |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
In the field of continual learning, models are designed to learn tasks one after the other. While most research has centered on supervised continual learning, recent studies have highlighted the strengths of self-supervised continual representation learning. The improved transferability of representations built with self-supervised methods is often associated with the role played by the multi-layer perceptron projector. In this work, we depart from this observation and reexamine the role of supervision in continual representation learning. We reckon that additional information, such as human annotations, should not deteriorate the quality of representations. Our findings show that supervised models when enhanced with a multi-layer perceptron head, can outperform self-supervised models in continual representation learning. |
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
xxx |
Approved |
no |
| Call Number |
Admin @ si @ MCT2023 |
Serial |
4013 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa |
| Title |
A model based pedestrian tracking review |
Type |
Report |
| Year |
2001 |
Publication |
CVC Technical Report #69 |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
CVC (UAB) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
invisible;ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ Pon2001 |
Serial |
522 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa |
| Title |
Model-Based Visual Localisation of Contours and Vehicles |
Type |
Book Whole |
| Year |
2007 |
Publication |
PhD Thesis, Universitat Autonoma de Barcelona-CVC |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
Phd Thesis |
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
Ph.D. thesis |
| Publisher |
Ediciones Graficas Rey |
Place of Publication |
|
Editor |
Antonio Lopez;Xavier Roca |
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
978-84-935251-3-2 |
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ Pon2007 |
Serial |
1107 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa; A.F. Sole; Antonio Lopez; Cristina Cañero; Petia Radeva; Jordi Vitria |
| Title |
Regularized EM |
Type |
Miscellaneous |
| Year |
1999 |
Publication |
Proceedings of the VIII Symposium Nacional de Reconocimiento de Formas y Analisis de Imagenes |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
Bilbao |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
invisible;ADAS;OR;MILAB;MV |
Approved |
no |
| Call Number |
ADAS @ adas @ PSL1999 |
Serial |
4 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa; A.F. Sole; Antonio Lopez; Cristina Cañero; Petia Radeva; Jordi Vitria |
| Title |
Regularized EM. |
Type |
Miscellaneous |
| Year |
2000 |
Publication |
Pattern Recognition and Applications, IOS Press, 69–77. |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
|
| Keywords |
|
| Abstract |
|
| Address |
|
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
invisible;ADAS;OR;MILAB;MV |
Approved |
no |
| Call Number |
ADAS @ adas @ PSL2000 |
Serial |
336 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa; Antonio Lopez |
| Title |
Vehicle Trajectory Estimation based on Monocular Vision |
Type |
Conference Article |
| Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
587-594 |
| Keywords |
vehicle detection |
| Abstract |
|
| Address |
Girona (Spain) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ PoL2007a |
Serial |
785 |
| Permanent link to this record |
| |
|
| |
| Author |
Daniel Ponsa; Antonio Lopez |
| Title |
Feature Selection Based on a New Formulation of the Minimal-Redundancy-Maximal-Relevance Criterion |
Type |
Conference Article |
| Year |
2007 |
Publication |
3rd Iberian Conference on Pattern Recognition and Image Analysis, LNCS 4477 |
Abbreviated Journal |
|
| Volume |
|
Issue |
|
Pages |
47-54 |
| Keywords |
|
| Abstract |
|
| Address |
Girona (Spain) |
| Corporate Author |
|
Thesis |
|
| Publisher |
|
Place of Publication |
|
Editor |
|
| Language |
|
Summary Language |
|
Original Title |
|
| Series Editor |
|
Series Title |
|
Abbreviated Series Title |
|
| Series Volume |
|
Series Issue |
|
Edition |
|
| ISSN |
|
ISBN |
|
Medium |
|
| Area |
|
Expedition |
|
Conference |
|
| Notes |
ADAS |
Approved |
no |
| Call Number |
ADAS @ adas @ PoL2007b |
Serial |
787 |
| Permanent link to this record |
