A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Filters
Datasets and Benchmarks for Densely Sampled 4D Light Fields
[article]
2013
International Symposium on Vision, Modeling, and Visualization
Preserved Fulltext
The data is characterised by a dense sampling of the light fields, which best fits current plenoptic cameras and is a characteristic property not found in current multi-view stereo benchmarks. ...
We present a new benchmark database to compare and evaluate existing and upcoming algorithms which are tailored to light field processing. ...
To alleviate the above shortcomings, we present a new benchmark database which consists at the moment of 13 high quality densely sampled light fields. ...
doi:10.2312/pe.vmv.vmv13.225-226
dblp:conf/vmv/WannerMG13
fatcat:blxxtlyf3fczflkxo5toa3ej4q
A Study of Efficient Light Field Subsampling and Reconstruction Strategies
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this paper, we study subsampling and reconstruction strategies for light fields. ...
Limited angular resolution is one of the main obstacles for practical applications of light fields. ...
As for the synthetic LF dataset, all 28 light fields from the HCI benchmark [Honauer et al., 2016] were used. 10 light fields in total were selected from these datasets as the test set and the rest as ...
arXiv:2008.04694v1
fatcat:broru4bffvhojc7bzbswdob7le
Depth-based refocusing for reducing directional aliasing artifacts
2016
Optics Express
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is text/html.
Meister, and B. Goldluecke, “Datasets and benchmarks for densely sampled 4D light fields,” in Proceedings of Vision Modeling and Visualization (VMV, 2013), pp. 225–226. S. Wanner and B. ...
Meister, and B. Goldluecke, “Datasets and benchmarks for densely sampled 4D light fields,” in Proceedings of Vision Modeling and Visualization (VMV, 2013), pp. 225–226. S. Wanner and B. ...
doi:10.1364/oe.24.028065
pmid:27906372
fatcat:we5zlqcjwje4hbdgz3jvq43w2q
Fast and Efficient Depth Map Estimation from Light Fields
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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
Sparse to Dense Scene Flow Estimation From Light Fields
2019
2019 IEEE International Conference on Image Processing (ICIP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
A dataset of synthetic video light fields created for assessing scene flow estimation techniques is also described. ...
The paper addresses the problem of scene flow estimation from sparsely sampled video light fields. ...
EVALUATION
Scene Flow Dataset For our experiments, we have prepared a synthetic video Light Field dataset 1 . ...
doi:10.1109/icip.2019.8803520
dblp:conf/icip/DavidPG19
fatcat:wc6y2a24nrg2dgy7qmrwpkjmzu
Dense Light Field Reconstruction From Sparse Sampling Using Residual Network
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
Besides, reconstructing a large amount of light rays equivalent to multiple light fields using sparse sampling arises a severe challenge for existing methods. ...
A light field records numerous light rays from a real-world scene. However, capturing a dense light field by existing devices is a time-consuming process. ...
highest among light field benchmark datasets so far. ...
arXiv:1806.05506v2
fatcat:ckdsvcr5l5efzf26bgmrdmt4si
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
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
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. ...
This paper introduces a novel deep network for estimating depth maps from a light field image. ...
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
Flexible Light Field Angular Superresolution via a Deep Coarse-to-Fine Framework
2022
Wireless Communications and Mobile Computing
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is application/pdf.
Acquisition of densely-sampled light fields (LFs) is challenging. ...
In this paper, we develop a coarse-to-fine light field angular superresolution that reconstructs densely-sampled LFs from sparsely-sampled ones. ...
SQ2020YFF0426386), and the Fundamental Research Funds for the Central Universities (Grant Nos. CUC19ZD006 and CUC21GZ007). ...
doi:10.1155/2022/4570755
fatcat:k3ijs4abkrgfthshjfjjms7rz4
Self-supervised Light Field View Synthesis Using Cycle Consistency
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
However, collecting such large datasets for light fields is challenging compared to natural images or videos. ...
The proposed method aims to transfer prior knowledge learned from high quality natural video datasets to the light field view synthesis task, which reduces the need for labeled light field data. ...
For this purpose, we use a variety of real-world and synthetic dense light field datasets which we sub-sample to create our test sparse datasets with sampling ratios α = 2 and α = 4. ...
arXiv:2008.05084v1
fatcat:4vyotfvkfbbp5oao5m533sv2h4
Self-supervised Light Field View Synthesis Using Cycle Consistency
2020
2020 IEEE 22nd International Workshop on Multimedia Signal Processing (MMSP)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
However, collecting such large datasets for light fields is challenging compared to natural images or videos. ...
The proposed method aims to transfer prior knowledge learned from high quality natural video datasets to the light field view synthesis task, which reduces the need for labeled light field data. ...
For this purpose, we use a variety of real-world and synthetic dense light field datasets which we sub-sample to create our test sparse datasets with sampling ratios α = 2 and α = 4. ...
doi:10.1109/mmsp48831.2020.9287105
fatcat:e7oqiqqlprellew2wcie7icz44
Fast and Accurate Optical Flow based Depth Map Estimation from Light Fields
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Depth map estimation is a crucial task in computer vision, and new approaches have recently emerged taking advantage of light fields, as this new imaging modality captures much more information about the ...
In this paper, we propose a novel depth estimation method from light fields based on existing optical flow estimation methods. ...
We evaluate here the accuracy and efficiency of our proposed method against stateof-the-art light field depth map estimation methods [26, 11, 28, 25, 10, 22, 19] using the recent HCI 4D light field dataset ...
arXiv:2008.04673v1
fatcat:no6ekcoqwnfyfouo7ym3gyvq7i
Light Field Scale-Depth Space Transform for Dense Depth Estimation
2014
2014 IEEE Conference on Computer Vision and Pattern Recognition Workshops
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Experimental results on the HCI (Heidelberg Collaboratory for Image Processing) light field benchmark show that our method gives state of the art depth accuracy. ...
We first propose a method for construction of light field scale-depth spaces, by convolving a given light field with a special kernel adapted to the light field structure. ...
Conclusions We have presented a novel method for dense depth estimation from light fields, based on extrema detection in continuous light field scale-depth spaces built upon the normalized second derivative ...
doi:10.1109/cvprw.2014.71
dblp:conf/cvpr/TosicB14
fatcat:7om7hieds5ayhg2766hfru6bvi
𝕏Resolution Correspondence Networks
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Other Versions
In this paper, we aim at establishing accurate dense correspondences between a pair of images with overlapping field of view under challenging illumination variation, viewpoint changes, and style differences ...
Through an extensive ablation study of the state-of-the-art correspondence networks, we surprisingly discovered that the widely adopted 4D correlation tensor and its related learning and processing modules ...
Acknowledgements We would like to thank Umar Ahmed, Guy Newsom and the rest of the XYZ Reality team for helping out with various design concepts and fruitful discussions. ...
arXiv:2012.09842v2
fatcat:urcvdjpzfbepnl4b5yd6u2bwou
Light Field Saliency Detection with Deep Convolutional Networks
[article]
2019
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
This makes our dataset suitable for training deeper networks and benchmarking. Furthermore, we propose a novel end-to-end CNN-based framework for light field saliency detection. ...
Compared to current light field saliency datasets [1], [2], our new dataset is larger, of higher quality, contains more variation and more types of light field inputs. ...
In order to directly synthesize novel views of dense 4D light fields from sparse views, Wang et al. ...
arXiv:1906.08331v2
fatcat:3xbuj443rvemdffwjdkw4garem
Compressive Light Field Reconstructions using Deep Learning
[article]
2018
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Light field imaging is limited in its computational processing demands of high sampling for both spatial and angular dimensions. ...
We present a deep learning approach using a new, two branch network architecture, consisting jointly of an autoencoder and a 4D CNN, to recover a high resolution 4D light field from a single coded 2D image ...
Acknowledgements: The authors would like to thank the anonymous reviewers for their detailed feedback, Siva Sankalp for running some experiments, and Mark Buckler for GPU computing support. ...
arXiv:1802.01722v1
fatcat:h4calra7hbd6vpqvs7yczbuhhm
« Previous
Showing results 1 — 15 out of 1,840 results