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Total variation-based dense depth from multicamera array
2018
Optical Engineering: The Journal of SPIE
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This paper presents a novel framework that generates a high-quality continuous depth map from multi-camera array/light field cameras. ...
Evaluation of this method based on a well-known benchmark indicates that the proposed framework performs well in terms of accuracy when compared to the top-ranked depth estimation methods and a baseline ...
Light Field Depth Estimation and Stereo Framework Kim et al. [30] proposed a framework to generate stereo images from a set of light field data. ...
doi:10.1117/1.oe.57.6.063105
fatcat:s4vzixo6abhghek4e7j4ssx5em
Attention-Based View Selection Networks for Light-Field Disparity Estimation
2020
PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
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This paper introduces a novel deep network for estimating depth maps from a light field image. ...
Experiments show that the proposed method achieves state-of-the-art performance in terms of accuracy and ranks the first on a popular benchmark for disparity estimation for light field images. ...
Acknowledgements This work was supported in part by Ministry of Science and Technology (MOST) and MOST Joint Research Center for ...
doi:10.1609/aaai.v34i07.6888
fatcat:bkebmzfv3jbjrhzh2d4aay3fku
Fast and Efficient Depth Map Estimation from Light Fields
[article]
2018
arXiv
pre-print
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The paper presents an algorithm for depth map estimation from the light field images in relatively small amount of time, using only single thread on CPU. ...
The proposed method improves existing principle of line fitting in 4-dimensional light field space. Line fitting is based on color values comparison using kernel density estimation. ...
The authors are grateful to Vladislav Golyanik, Kiran Varanasi and Jonathan Wray for the provided help. ...
arXiv:1805.00264v1
fatcat:ork5dh2xtzdupmo75ld6wzxjka
Light Field Intrinsics with a Deep Encoder-Decoder Network
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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We present a fully convolutional autoencoder for light fields, which jointly encodes stacks of horizontal and vertical epipolar plane images through a deep network of residual layers. ...
We provide an extensive evaluation on synthetic light field data, and show that the network yields good results on previously unseen real world data captured by a Lytro Illum camera and various gantries ...
Acknowledgments This work was supported by the ERC Starting Grant "Light Field Imaging and Analysis" (LIA 336978, FP7-2014). ...
doi:10.1109/cvpr.2018.00953
dblp:conf/cvpr/AlperovichJSG18
fatcat:hxboolz3bnfxfhmzw7divribxa
Rapid Light Field Depth Estimation with Semi-Global Matching
[article]
2019
arXiv
pre-print
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Running time of the light field depth estimation algorithms is typically high. This assessment is based on the computational complexity of existing methods and the large amounts of data involved. ...
In this context, we propose an approach, which involves Semi-Global Matching for the processing of light field images. ...
The authors are grateful to Kiran Varanasi and Jonathan Wray for the provided support. ...
arXiv:1907.13449v1
fatcat:ctokovsfbzd77dwl5fvlrhzlyy
Learning to Think Outside the Box: Wide-Baseline Light Field Depth Estimation with EPI-Shift
2019
2019 International Conference on 3D Vision (3DV)
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2019 pre-print arXiv:1909.09059v1 fatcat:kvawngyffncb3cfkoy2qsl7kkq
We propose a method for depth estimation from light field data, based on a fully convolutional neural network architecture. ...
Our goal is to design a pipeline which achieves highly accurate results for small- and wide-baseline light fields. ...
We thank the Center for Information Services and High Performance Computing (ZIH) at TU Dresden for generous allocations of computer time. ...
doi:10.1109/3dv.2019.00036
dblp:conf/3dim/LeistnerSMGR19
fatcat:eewtvohxjzexvhxd6zvhqugojm
Fast Depth Estimation for Light Field Cameras
2020
IEEE Transactions on Image Processing
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As most of these applications use depth information, depth estimation from a light field image is an important topic for light field image processing research. ...
Fast Depth Estimation for Light Field Cameras Kazu Mishiba , Member, IEEE Abstract-Fast depth estimation for light field images is an important task for multiple applications such as image-based rendering ...
doi:10.1109/tip.2020.2970814
fatcat:s55cax4fabgzthwvhzgnovb464
Fast and Accurate 3D Measurement Based on Light-Field Camera and Deep Learning
2019
Sensors
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from one single light-field image captured by one single light-field camera. ...
Meanwhile, our network has achieved similar or better performance in other regions for both synthetic light-field images and real-world data compared to the state-of-the-art algorithms. ...
With these advantages, various algorithms [6] [7] [8] have been developed to estimate depth information from single light-field image. ...
doi:10.3390/s19204399
fatcat:34nbga2iwbfchpscq63s44fwae
Deep Depth From Focus
[article]
2018
arXiv
pre-print
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In this paper, we propose 'Deep Depth From Focus (DDFF)' as the first end-to-end learning approach to this problem. One of the main challenges we face is the hunger for data of deep neural networks. ...
In order to obtain a significant amount of focal stacks with corresponding groundtruth depth, we propose to leverage a light-field camera with a co-calibrated RGB-D sensor. ...
for DFF, but also for other tasks such as depth from light-field or 3d reconstruction from light-field. ...
arXiv:1704.01085v3
fatcat:6rcoj7xlzvaghdpdbfw4m75baq
Trust your Model: Light Field Depth Estimation with Inline Occlusion Handling
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
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We address the problem of depth estimation from lightfield images. Our main contribution is a new way to handle occlusions which improves general accuracy and quality of object borders. ...
We have evaluated our method on a public light-field dataset, where we achieve state-of-the-art results in nine out of twelve error metrics, with a close tie for the remaining three. ...
for Image Processing (HCI). ...
doi:10.1109/cvpr.2018.00476
dblp:conf/cvpr/SchillingDRJ18
fatcat:q6h3ymaxi5hnxktxis5p3sdvce
Nonlinear Optimization of Light Field Point Cloud
2022
Sensors
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Light field depth estimation utilizes many observations of the scene and hence can provide accurate reconstruction. ...
Together with that we reformulate the reconstruction result to a form of point cloud from different light field viewpoints and propose a non-linear optimization of it. ...
Related Work Many methods exist for solving the light field depth estimation task. ...
doi:10.3390/s22030814
pmid:35161563
pmcid:PMC8838410
fatcat:tr4kfymnqbhmldq6bgkx6tshf4
Light Field Salient Object Detection: A Review and Benchmark
[article]
2021
arXiv
pre-print
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Besides, due to the inconsistency of datasets in their current forms, we further generate complete data and supplement focal stacks, depth maps and multi-view images for the inconsistent datasets, making ...
This paper provides the first comprehensive review and benchmark for light field SOD, which has long been lacking in the saliency community. ...
The light-field flow was first employed in this method, estimated from focal stacks and multi-view sequences, to capture depth discontinuities/contrast. ...
arXiv:2010.04968v4
fatcat:gvwnnhd4m5hlfjaamuupe7ymva
EPI-based Oriented Relation Networks for Light Field Depth Estimation
[article]
2020
arXiv
pre-print
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Benefiting from this property of EPIs, some representative methods estimate depth maps by analyzing the disparity of each line in EPIs. ...
To facilitate training, we also propose a refocusing-based data augmentation method to obtain different slopes from EPIs of the same scene point. ...
of depth estimation from light fields. ...
arXiv:2007.04538v2
fatcat:riddw7xkyvdutjbjwasussgozy
BOP: Benchmark for 6D Object Pose Estimation
[article]
2018
arXiv
pre-print
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We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. ...
The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. ...
, No. 16-072105: Complex network methods applied to ancient Egyptian data in the Old Kingdom (2700-2180 BC). ...
arXiv:1808.08319v1
fatcat:k6bmka24ybdytnzxdf2vbcco6q
BOP: Benchmark for 6D Object Pose Estimation
[chapter]
2018
Lecture Notes in Computer Science
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We propose a benchmark for 6D pose estimation of a rigid object from a single RGB-D input image. ...
The training data consists of a texture-mapped 3D object model or images of the object in known 6D poses. ...
, No. 16-072105: Complex network methods applied to ancient Egyptian data in the Old Kingdom (2700-2180 BC). ...
doi:10.1007/978-3-030-01249-6_2
fatcat:vfcllj6debaznkp3gdg7frfbwm
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