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Front Matter: Volume 11049
2019
International Workshop on Advanced Image Technology (IWAIT) 2019
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deep residual networks for image super-resolution 11049 09 3D scene reconstruction and object recognition for indoor scene
SPECIAL SESSION II
0A A support system for archiving antique stereographs ...
of lateral resolution in synthetic aperture super-resolution ultrasound imaging ix Proc. of SPIE Vol. 11049 1104901-9 Estimation of objective understanding measure based on student's nonverbal behavior ...
doi:10.1117/12.2530762
fatcat:lwxupqdakfhtdjxznvtohfj7di
Video Super Resolution Based on Deep Learning: A Comprehensive Survey
[article]
2022
arXiv
pre-print
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In this survey, we comprehensively investigate 33 state-of-the-art video super-resolution (VSR) methods based on deep learning. ...
It is well known that the leverage of information within video frames is important for video super-resolution. ...
Yaowei Wang (Associate Professor with Peng Cheng Laboratory, Shenzhen, China) for their help in improving the quality of this manuscript. ...
arXiv:2007.12928v3
fatcat:nxoejcfdnzas3jznbqsale36ty
CNN-Based Macropixel-level Up-sampling for Plenoptic Image Coding
2019
IEEE Access
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With the insertion of a microlens array, plenoptic cameras can record both angular and spatial information of a scene on a plenoptic image. ...
First, a macropixel-based down-sampling method, which performs the down-sampling in the units of macropixels, is developed for reducing the block resolution. ...
Compared with conventional 2D technology, 3D technology requires richer stereo information of 3D scenes [3] , [4] . ...
doi:10.1109/access.2019.2922670
fatcat:edllnuje7rcmdo6q6qw675gjoy
Light Field Image Compression via CNN-Based EPI Super-Resolution and Decoder-Side Quality Enhancement
2019
IEEE Access
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Because of the capacity of capturing both the spatial and angular information of the light rays simultaneously, light field images (LFIs) contain richer scene information compared with conventional images ...
The low-resolution EPIs generated from the sparse SAIs are super-resolved by a CNN and the outputs, high-resolution EPIs, are used to rebuild the dense SAIs. ...
CNN-BASED SINGLE IMAGE SUPER-RESOLUTION A critical step in the proposed sparse coding framework is EPI super-resolution, so here is a brief introduction to the work of CNN-based single image super-resolution ...
doi:10.1109/access.2019.2930644
fatcat:xjj63zrdrncltbhtmbvwp6hd2a
cvpaper.challenge in 2015 - A review of CVPR2015 and DeepSurvey
[article]
2016
arXiv
pre-print
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(TDU), and Univ. of Tsukuba that aims to systematically summarize papers on computer vision, pattern recognition, and related fields. ...
The "cvpaper.challenge" is a group composed of members from AIST, Tokyo Denki Univ. ...
In regard to the problem of super-resolution, a method using Self-Similarity based Super-Resolution was reported [563] . ...
arXiv:1605.08247v1
fatcat:cd4mc7uor5f2rpu3aketd6naf4
3D Appearance Super-Resolution With Deep Learning
2019
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
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On the other hand, the advent of deep learning-based methods has already a significant impact on the problem of video and image SR. ...
We introduce a 3D appearance SR (3DASR) dataset based on the existing ETH3D [42] , SyB3R [31] , MiddleBury, and our Collection of 3D scenes from TUM [21] , Fountain [51] and Relief [53] . ...
Figure 7 : 7 Figure 7: Network structure of (a) NLR and (b) NHR based on the the EDSR [36]. The change in the dimension of the blocks indicates the resolution change of the feature maps. ...
doi:10.1109/cvpr.2019.00990
dblp:conf/cvpr/LiTTPG19
fatcat:3im55qpcyvff3czj4ierq7tu7u
Survey of Deep-Learning Approaches for Remote Sensing Observation Enhancement
2019
Sensors
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In this paper, we provide a comprehensive review of deep-learning methods for the enhancement of remote sensing observations, focusing on critical tasks including single and multi-band super-resolution ...
Less yet equally important effort has also been allocated to addressing the challenges associated with the enhancement of low-quality observations from remote sensing platforms. ...
In [91] , a CNN architecture based on the VDSR [31] is explored for super-resolution of video satellite frames. ...
doi:10.3390/s19183929
fatcat:fp7lezjwcfg5fol5hxmgoejg7a
Compressed-domain video classification with deep neural networks: "There's way too much information to decode the matrix"
2017
2017 IEEE International Conference on Image Processing (ICIP)
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changes in each video scene. ...
We investigate video classification via a 3D deep convolutional neural network (CNN) that directly ingests compressed bitstream information. ...
As exemplified in numerous works [16, 9] , the advantage of using a 3D CNN architecture with a 4D input, versus stacking the frames as channels and using a 3D input of size N × N × KT with a 2D CNN, is ...
doi:10.1109/icip.2017.8296598
dblp:conf/icip/ChadhaAA17
fatcat:jtsdez5crfbanj2dfotbfagtay
Efficient Geometry-aware 3D Generative Adversarial Networks
[article]
2022
arXiv
pre-print
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2021 pre-print arXiv:2112.07945v1 fatcat:czilifpuzvhxrdgtxpz5qucevm
We demonstrate state-of-the-art 3D-aware synthesis with FFHQ and AFHQ Cats, among other experiments. ...
In this work, we improve the computational efficiency and image quality of 3D GANs without overly relying on these approximations. ...
We thank Alex Chan, Giap Nguyen, and Trevor Chan for help with figures and diagrams. ...
arXiv:2112.07945v2
fatcat:diysjwesgfbl7hlf2yn3s3lhb4
3D Appearance Super-Resolution with Deep Learning
[article]
2019
arXiv
pre-print
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On the other hand, the advent of deep learning-based methods has already a significant impact on the problem of video and image SR. ...
We introduce a 3D appearance SR (3DASR) dataset based on the existing ETH3D [42], SyB3R [31], MiddleBury, and our Collection of 3D scenes from TUM [21], Fountain [51] and Relief [53]. ...
Figure 7 : 7 Network structure of (a) NLR and (b) NHR based on the the EDSR [36] . The change in the dimension of the blocks indicates the resolution change of the feature maps. ...
arXiv:1906.00925v2
fatcat:5rpefoimmbfkrjdjwvy4kjpggu
Light Field Image Processing: An Overview
2017
IEEE Journal on Selected Topics in Signal Processing
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We focus on all aspects of light field image processing, including basic light field representation and theory, acquisition, super-resolution, depth estimation, compression, editing, processing algorithms ...
On the one hand, this higher-dimensional representation of visual data offers powerful capabilities for scene understanding, and substantially improves the performance of traditional computer vision problems ...
Angular Super-resolution Many studies have focused on angular super-resolution using a small set of views with high spatial resolution. ...
doi:10.1109/jstsp.2017.2747126
fatcat:rvsfzvdxbbf4zesqdkaj3cseza
Video Classification With CNNs: Using The Codec As A Spatio-Temporal Activity Sensor
[article]
2017
arXiv
pre-print
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In order to evaluate the accuracy of a video classification framework based on such activity data, we independently train two CNN architectures on MB texture and MV correspondences and then fuse their ...
Our approach begins with the observation that all modern video codecs divide the input frames into macroblocks (MBs). ...
MV-based CNN approach have been presented in our corresponding conference paper [20] , MV-based selective MB texture decoding and the fusion of the temporal 3D-CNN with a spatial CNN are proposed here ...
arXiv:1710.05112v2
fatcat:yaxmhmffbjh4xfbjbsk2rtxdky
SASRT: Semantic-Aware Super-Resolution Transmission for Adaptive Video Streaming over Wireless Multimedia Sensor Networks
2019
Sensors
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However, identifying semantic information on the user side may increase the computational cost of the user side. On the user side, video quality is enriched with super-resolution technologies. ...
In this paper, a semantic-aware super-resolution transmission for adaptive video streaming system (SASRT) for WMSNs is presented. ...
The algorithm improves the super-resolution video efficiency based on video characteristics such as timing. ...
doi:10.3390/s19143121
fatcat:yemwbxmiuvfoja57aszqjebahi
Review of light field technologies
2021
Visual Computing for Industry, Biomedicine, and Art
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) scene reconstruction and view synthesis, and (5) industrial products because the technologies of lights fields also intersect with industrial applications. ...
In this article, light field imaging is reviewed from the following aspects with an emphasis on the achievements of the past five years: (1) depth estimation, (2) content editing, (3) image quality, (4 ...
Acknowledgements The authors are grateful to Kuaishou Technology, University of California, Berkeley, and Tsinghua University. ...
doi:10.1186/s42492-021-00096-8
pmid:34862574
pmcid:PMC8642475
fatcat:6rq5rx5svrcerdr7rciaijy3k4
Multimodal Low Resolution Face and Frontal Gait Recognition from Surveillance Video
2021
Electronics
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Moreover, the classification accuracy on high-resolution face images is considerably higher. ...
Biometric identification using surveillance video has attracted the attention of many researchers as it can be applicable not only for robust identification but also personalized activity monitoring. ...
Conflicts of Interest: The authors declare no conflict of interest. ...
doi:10.3390/electronics10091013
doaj:46769ed6fbf842c8ac68ffb373934346
fatcat:bebdizpu3jcl3odzsw3zcgeaym
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