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ActiveStereoNet: End-to-End Self-Supervised Learning for Active Stereo Systems
[article]
2018
arXiv
pre-print
Preserved Fulltext
In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. ...
Due to the lack of ground truth, our method is fully self-supervised, yet it produces precise depth with a subpixel precision of 1/30th of a pixel; it does not suffer from the common over-smoothing issues ...
This paper proposes the first end-to-end deep learning approach for active stereo that is trained fully self-supervised. ...
arXiv:1807.06009v1
fatcat:g4su4zk37jdpblr4xubxuihbii
ActiveStereoNet: End-to-End Self-supervised Learning for Active Stereo Systems
[chapter]
2018
Lecture Notes in Computer Science
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In this paper we present ActiveStereoNet, the first deep learning solution for active stereo systems. ...
Due to the lack of ground truth, our method is fully self-supervised, yet it produces precise depth with a subpixel precision of 1/30th of a pixel; it does not suffer from the common over-smoothing issues ...
This paper proposes the first end-to-end deep learning approach for active stereo that is trained fully self-supervised. ...
doi:10.1007/978-3-030-01237-3_48
fatcat:wt3edayygjg5fd7jsk5xlu4cam
Self-Supervised Depth Completion for Active Stereo
[article]
2022
arXiv
pre-print
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These depth sensors, however, suffer from stereo artefacts and do not provide dense depth estimates.In this work, we present the first self-supervised depth completion method for active stereo systems ...
Due to the nonexistence of publicly available active stereo datasets, we release a real dataset together with additional information for a publicly available synthetic dataset (TartanAir [42]) needed for ...
CONCLUSIONS In this work we investigate self-supervised depth completion for active stereo systems. ...
arXiv:2110.03234v2
fatcat:mw2ekgmigzfbbhjdihuxn2j7mm
ActiveZero: Mixed Domain Learning for Active Stereovision with Zero Annotation
[article]
2021
arXiv
pre-print
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In this paper we present a new framework, ActiveZero, which is a mixed domain learning solution for active stereovision systems that requires no real world depth annotation. ...
Finally, we show how the method can be trained end-to-end and that each module is important for attaining the end result. ...
This paper proposes an end-to-end learning stereo method that combines the advantages of self-supervised learning in the real domain and supervised learning in the simulation domain which we call mixed ...
arXiv:2112.02772v1
fatcat:cdnm4mmzdfab7jshdehzbpnmsu
Advances and Prospects of Vision-Based 3D Shape Measurement Methods
2022
Machines
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Specifically, the basic principles and typical techniques of triangulation-based measurement methods as well as their advantages and limitations are elaborated, and the learning-based techniques used for ...
Vision-based three-dimensional (3D) shape measurement techniques have been widely applied over the past decades in numerous applications due to their characteristics of high precision, high efficiency ...
[128] realized an end-to-end deep learning-based scheme for FPP systems. ...
doi:10.3390/machines10020124
fatcat:ws3pbwv6wzcole5jtca35c5fjm
SteReFo: Efficient Image Refocusing with Stereo Vision
[article]
2019
arXiv
pre-print
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To this end, high quality optical systems are used in DSLR cameras to focus on a specific depth plane while producing visually pleasing bokeh. ...
It also enables computational video focus tracking for moving objects in addition to refocusing of static images. ...
Its successor [56] extends the work with self-supervision to the domain of active sensing while maintaining the core efficiency. We build upon their work to leverage this computational advantage. ...
arXiv:1909.13395v1
fatcat:pygdnjn3pre3hj2dlynu5ftkim
SteReFo: Efficient Image Refocusing with Stereo Vision
2019
2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)
Preserved Fulltext
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To this end, high quality optical systems are used in DSLR cameras to focus on a specific depth plane while producing visually pleasing bokeh. ...
It also enables computational video focus tracking for moving objects in addition to refocusing of static images. ...
Its successor [56] extends the work with self-supervision to the domain of active sensing while maintaining the core efficiency. We build upon their work to leverage this computational advantage. ...
doi:10.1109/iccvw.2019.00411
dblp:conf/iccvw/BusamHMS19
fatcat:7oxfmmmgd5afjaaq4aztngcbye
HITNet: Hierarchical Iterative Tile Refinement Network for Real-time Stereo Matching
[article]
2021
arXiv
pre-print
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At the time of writing, HITNet ranks 1st-3rd on all the metrics published on the ETH3D website for two view stereo, ranks 1st on most of the metrics among all the end-to-end learning approaches on Middlebury-v3 ...
This paper presents HITNet, a novel neural network architecture for real-time stereo matching. ...
We would like to thank Shahram Izadi for support and enabling of this project. ...
arXiv:2007.12140v3
fatcat:nj63vbvjdjgbvc5oh6pluq7v5u
Depth Estimation by Combining Binocular Stereo and Monocular Structured-Light
[article]
2022
arXiv
pre-print
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It is well known that the passive stereo system cannot adapt well to weak texture objects, e.g., white walls. However, these weak texture targets are very common in indoor environments. ...
In order to verify the effectiveness of the proposed system, we build a prototype and collect a test dataset in indoor scenes. ...
ActiveStereoNet [47] is the first deep learning solution for active stereo systems. Due to the lack of ground truth, the network is designed to be fully self-supervised. ...
arXiv:2203.10493v1
fatcat:vj7rzbbewna2faw7ttfzozc5hm