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Interest point detectors stability evaluation on ApolloScape dataset
[article]
2018
arXiv
pre-print
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To this end, we evaluate stability of a number of hand crafted and recent, learning-based interest point detectors on the street-level view ApolloScape dataset. ...
In this paper we verify if the recent, deep-learning based interest point detectors have the advantage over the traditional, hand-crafted keypoint detectors. ...
Acknowledgement This research was supported by Google Sponsor Research Agreement under the project "Efficient visual localization on mobile devices". ...
arXiv:1809.11039v1
fatcat:srbhj4mcfzgtfiwtailij64zaa
Interest Point Detectors Stability Evaluation on ApolloScape Dataset
[chapter]
2019
Lecture Notes in Computer Science
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To this end, we evaluate stability of a number of hand crafted and recent, learning-based interest point detectors on the street-level view ApolloScape dataset. ...
In this paper we verify if the recent, deep-learning based interest point detectors have the advantage over the traditional, hand-crafted keypoint detectors. ...
Acknowledgement This research was supported by Google Sponsor Research Agreement under the project "Efficient visual localization on mobile devices". ...
doi:10.1007/978-3-030-11021-5_45
fatcat:hyhk7g6p5vemzmjvpoyrug6gxu
Robust Learning Through Cross-Task Consistency
[article]
2020
arXiv
pre-print
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The evaluations are performed on multiple datasets, including Taskonomy, Replica, CocoDoom, and ApolloScape, and they benchmark cross-task consistency versus various baselines including conventional multi-task ...
The proposed formulation is based on inference-path invariance over a graph of arbitrary tasks. ...
Consistency Energy as a Domain Shift Detector: Plot 8(c) shows the energy distribution of in-distribution (Taskonomy) and out-of-distribution datasets (ApolloScape, CocoDoom). ...
arXiv:2006.04096v1
fatcat:uuk7yaowtfgljk6bcoivo5oi6u
JRDB: A Dataset and Benchmark of Egocentric Visual Perception for Navigation in Human Environments
[article]
2020
arXiv
pre-print
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The dataset includes 64 minutes of annotated multimodal sensor data including stereo cylindrical 360^∘ RGB video at 15 fps, 3D point clouds from two Velodyne 16 Lidars, line 3D point clouds from two Sick ...
With this dataset, which we plan on extending with further types of annotation in the future, we hope to provide a new source of data and a test-bench for research in the areas of egocentric robot vision ...
EVALUATION In this section, we evaluate the performance of several state-of-theart/popular approaches for detection and tracking on the egocentric data of the JRDB dataset. ...
arXiv:1910.11792v2
fatcat:wquzzegmznh2vasn2z3trkugsq
VIL-100: A New Dataset and A Baseline Model for Video Instance Lane Detection
[article]
2021
arXiv
pre-print
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Experiments on the new collected dataset show that the proposed MMA-Net outperforms state-of-the-art lane detection methods and video object segmentation methods. ...
While car cameras always take streaming videos on the way, current lane detection works mainly focus on individual images (frames) by ignoring dynamics along the video. ...
BDD100K and ApolloScape are two large-scale video datasets for driving. ...
arXiv:2108.08482v1
fatcat:oplr3wbjt5fbhlltdsp7bovapi
Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overview
[article]
2022
arXiv
pre-print
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Comparative results of current state-of-the-art methods on several publicly available datasets are also presented, together with insightful observations and inspiring future research directions. ...
In our work, metrics, datasets, and methods of both detection and tracking are presented in detail. ...
While existing (RGB)D-based methods are all evaluated on datasets with dense point clouds generated from depth maps, their performances on sparse point clouds are under explored, and this has caused a ...
arXiv:2105.14291v2
fatcat:2kxd4owthvf7tbcbnlqlqu4r3m
Image Matching from Handcrafted to Deep Features: A Survey
2020
International Journal of Computer Vision
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In addition, we also provide a comprehensive and objective comparison of these classical and latest techniques through extensive experiments on representative datasets. ...
Following the feature-based image matching pipeline, we first introduce feature detection, description, and matching techniques from handcrafted methods to trainable ones and provide an analysis of the ...
Komorowski et al. (2018) provided a stability evaluation for handcrafted and learning-based interest point detectors on ApolloScape street dataset . ...
doi:10.1007/s11263-020-01359-2
fatcat:a2epfaolwjfm5mcrsmn7g6sd7m
Computer Vision for Autonomous Vehicles: Problems, Datasets and State of the Art
[article]
2021
arXiv
pre-print
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2019 pre-print arXiv:1704.05519v2 fatcat:vg2fezsgyzgptbpbvnwcpw24qyOther Versions
This book attempts to narrow this gap by providing a survey on the state-of-the-art datasets and techniques. ...
While several survey papers on particular sub-problems have appeared, no comprehensive survey on problems, datasets, and methods in computer vision for autonomous vehicles has been published. ...
[230] compare generic object detectors on the popular GTSDB dataset. ...
arXiv:1704.05519v3
fatcat:xiintiarqjbfldheeg2hsydyra
Toward a Computer Vision Perspective on the Visual Impact of Vegetation in Symmetries of Urban Environments
2018
Symmetry
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There are a lot of researches on ecological, architectural or aesthetic points of view to address this issue. ...
We statistically evaluate the correlations of the amount of vegetation with objective computer vision traits such as Fourier domain, color histogram, and estimated depth from monocular view. ...
applied on RGB images [46] WildDash [50] 70 -Mapillary [51] 25,000 -ApolloScape [47] 140,000 survey-grade dense 3D point cloud We propose the virtual RGBD green-city dataset provided as Supplementary ...
doi:10.3390/sym10120666
fatcat:brylx5vlrzbb3dehskqd4ah2je
Efficient Deep Neural Networks
[article]
2019
arXiv
pre-print
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Data efficiency: we developed an advanced tool that enables 6.2x faster annotation of a LiDAR point cloud. ...
This dissertation focuses on the above problems and improving the efficiency of deep neural networks at four levels. ...
Together with the paper, we also open-sourced the code to train, evaluate, and run SqueezeDet models on KITTI [33] and new datasets. ...
arXiv:1908.08926v1
fatcat:qqcpeueypbdydmc3jfvx3lseqy
The MODISSA testbed: a multi-purpose platformfor the prototypical realization of vehicle-relatedapplications using optical sensors
2021
Applied Optics
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2021 pre-print arXiv:2105.13580v1 fatcat:ocatqvwkhzcqhnr7ltx6ujvdky
data analysis, and immediate visualization on in-car displays. ...
We present the current state of development of the sensor-equipped car MODISSA, with which Fraunhofer IOSB realizes a configurable experimental platform for hardware evaluation and software development ...
DISCLOSURES The authors declare no conflicts of interest. ...
doi:10.1364/ao.423599
pmid:34612862
fatcat:2djaotjzwbd3ndcai2h6zkjgjy
A Critical Analysis of Image-based Camera Pose Estimation Techniques
[article]
2022
arXiv
pre-print
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Furthermore, we summarise what are the popular datasets used for camera localization and compare the quantitative and qualitative results of these methods with detailed performance metrics. ...
In this survey, we first introduce specific application areas and the evaluation metrics for camera localization pose according to different sub-tasks (learning-based 2D-2D task, feature-based 2D-3D task ...
SuperPoint [66] , created a large dataset of pseudo-ground truth interest point locations in real images, supervised by the interest point detector itself. ...
arXiv:2201.05816v1
fatcat:5wskhyskivh5bh67icaj3pc5i4
Vehicle Telematics Via Exteroceptive Sensors: A Survey
[article]
2020
arXiv
pre-print
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For each of them, we report the most recent and important works relying on exteroceptive sensors, as long as the available datasets. ...
Then, we review in detail all exteroceptive sensors of some interest for vehicle telematics, highlighting advantages, drawbacks, and availability in off-the-shelf devices. ...
The system uses a linearly scanning method to evaluate the GLCM approach. To test the approach, marks are introduced using a vision dataset [96] . ...
arXiv:2008.12632v1
fatcat:lwzwvdldnbbmhlkwsjzipowfly
Zeus: A System Description of the Two-Time Winner of the Collegiate SAE AutoDrive Competition
[article]
2020
arXiv
pre-print
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This includes details on the team's organizational structure, sensor suite, software components, and performance at the Year 2 competition. ...
We trained our model on the large BDD100k dataset and tested on BDD's evaluation set (Yu et al., 2018) . ...
Other self-driving datasets include the Oxford Robotcar dataset (Maddern et al., 2017) , the ApolloScape dataset (Huang et al., 2018) , and NuScenes . ...
arXiv:2004.08752v1
fatcat:jm4os5mzirf7jaogd7a76nrvkq
A Survey of Autonomous Driving: Common Practices and Emerging Technologies
[article]
2020
arXiv
pre-print
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The paper concludes with an overview of available datasets and tools for ADS development. ...
Furthermore, the state-of-the-art was implemented on our own platform and various algorithms were compared in a real-world driving setting. ...
State-ofthe-art algorithms are currently being evaluated on the KITTI dataset [174] and nuScenes dataset [175] as they offer labeled 3D scenes. ...
arXiv:1906.05113v2
fatcat:2hqztllrgjhndbc5aebduvukai
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