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AIM 2020 Challenge on Rendering Realistic Bokeh
[article]
2020
arXiv
pre-print
Preserved Fulltext
This paper reviews the second AIM realistic bokeh effect rendering challenge and provides the description of the proposed solutions and results. ...
The participants had to render bokeh effect based on only one single frame without any additional data from other cameras or sensors. ...
Acknowledgments We thank the AIM 2020 sponsors: Huawei, MediaTek, Qualcomm, NVIDIA, Google and Computer Vision Lab / ETH Zürich. ...
arXiv:2011.04988v1
fatcat:taj54kntdbbmfpekn7cz6eqcqe
BGGAN: Bokeh-Glass Generative Adversarial Network for Rendering Realistic Bokeh
[article]
2020
arXiv
pre-print
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This approach ranked First in AIM 2020 Rendering Realistic Bokeh Challenge Track 1 & Track 2. ...
Meanwhile, the GAN-based method and perceptual loss are combined for rendering a realistic bokeh effect in the stage of finetuning the model. ...
dataset [8] was released by AIM 2020 Bokeh Effect Rendering Challenge. ...
arXiv:2011.02242v1
fatcat:eygyth566bdsbbbvoufj7xu4zy
Depth-aware Blending of Smoothed Images for Bokeh Effect Generation
[article]
2020
arXiv
pre-print
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The proposed approach is compared against a saliency detection based baseline and a number of approaches proposed in AIM 2019 Challenge on Bokeh Effect Synthesis. ...
This approach ranked second in AIM 2019 Bokeh effect challenge-Perceptual Track. ...
AIM 2019 Challenge on Bokeh Effect Synthesis The proposed solution participated in AIM 2019 Challenge on Bokeh Effect Synthesis which is a competition on example- PSNR ↑ SSIM ↑ LPIPS ↓ Phase
Efficiency ...
arXiv:2005.14214v1
fatcat:v6ktxifqi5f7poh5jv24tcst4i
Portraiture, Surveillance, and the Continuity Aesthetic of Blur
2021
Frames Cinema Journal
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For example, the 2020 AIM challenge for rendering a realistic blur used a Canon 7D dSLR camera as a base and attempted to create similar images algorithmically with smartphone cameras. 64 The process ...
A study on generating realistic bokeh notes specifically why selfies are a good candidate for training the algorithm to recognize human/data subjects. ...
doi:10.15664/fcj.v18i1.2249
fatcat:c6a3pqkgoncl3dr23ec7fukxui
AcED: Accurate and Edge-consistent Monocular Depth Estimation
[article]
2020
arXiv
pre-print
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Additionally, we demonstrate practical utility of the proposed method for single camera bokeh solution using in-house dataset of challenging real-life images. ...
Extensive evaluation of the proposed model on challenging benchmarks reveals its superiority over recent state-of-the-art methods, both quantitatively and qualitatively. ...
The depth maps generated by AcED on real life images were combined with our human segmentation mask [1] to apply realistic bokeh effect with varying background blur. ...
arXiv:2006.09243v1
fatcat:z2rk66hhbbb47mvf5ptwmrkyme
Defocus Blur Detection via Salient Region Detection Prior
[article]
2020
arXiv
pre-print
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In an image with bokeh effect, it is obvious that the salient region and the depth-of-field area overlap in most cases. ...
Defocus blur Detection aims to separate the out-of-focus and depth-of-field areas in photos, which is an important work in computer vision. ...
DBD is an essential work for many computer vision tasks, as it has latent relationships with several tasks, such as salient region detection [35] , rendering realistic bokeh [34] , quality assessment ...
arXiv:2011.09677v1
fatcat:gzexisrkarbenlw273igw26ehm
DriverGym: Democratising Reinforcement Learning for Autonomous Driving
[article]
2021
arXiv
pre-print
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Despite promising progress in reinforcement learning (RL), developing algorithms for autonomous driving (AD) remains challenging: one of the critical issues being the absence of an open-source platform ...
capable of training and effectively validating the RL policies on real-world data. ...
We would like to thank everyone at Level 5 working on data-driven planning, in particular Sergey Zagoruyko, Alborz Alavian, Oliver Scheel, Yawei Ye, Moritz Niendorf, Stefano Pini and Maciej Wołczyk. ...
arXiv:2111.06889v1
fatcat:t2yzmmb2fvd2lj4p4e77iakn54
AIM 2020 Challenge on Video Temporal Super-Resolution
[article]
2020
arXiv
pre-print
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This paper reports the second AIM challenge on Video Temporal Super-Resolution (VTSR), a.k.a. frame interpolation, with a focus on the proposed solutions, results, and analysis. ...
To simulate realistic and challenging dynamics in the real-world, we employ the REDS_VTSR dataset derived from diverse videos captured in a hand-held camera for training and evaluation purposes. ...
Acknowledgments We thank all AIM 2020 sponsors: Huawei Technologies Co. Ltd., MediaTek Inc., NVIDIA Corp., Qualcomm Inc., Google, LLC and CVL, ETH Zürich. ...
arXiv:2009.12987v1
fatcat:23cngd3i25bupb5lwszpzxthte
AIM 2020 Challenge on Learned Image Signal Processing Pipeline
[article]
2020
arXiv
pre-print
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This paper reviews the second AIM learned ISP challenge and provides the description of the proposed solutions and results. ...
The target metric used in this challenge combined fidelity scores (PSNR and SSIM) with solutions' perceptual results measured in a user study. ...
Acknowledgments We thank the AIM 2020 sponsors: Huawei, MediaTek, Qualcomm, NVIDIA, Google and Computer Vision Lab / ETH Zürich. ...
arXiv:2011.04994v1
fatcat:i43uj46xxfhcxgsg7e7l6qbvqe
Review of light field technologies
2021
Visual Computing for Industry, Biomedicine, and Art
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According to these achievements and challenges, in the near future, the applications of light fields could offer more portability, accessibility, compatibility, and ability to visualize the world. ...
State-of-the-art research has focused on light field acquisition, manipulation, and display. In addition, the research has extended from the laboratory to industry. ...
[62] proposed a light field refocusing method to improve bokeh rendering and image quality. They first estimated the disparity map and rendered the bokeh on the center-view sub-image. ...
doi:10.1186/s42492-021-00096-8
pmid:34862574
pmcid:PMC8642475
fatcat:6rq5rx5svrcerdr7rciaijy3k4
AIM 2020: Scene Relighting and Illumination Estimation Challenge
[article]
2020
arXiv
pre-print
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We review the AIM 2020 challenge on virtual image relighting and illumination estimation. ...
This paper presents the novel VIDIT dataset used in the challenge and the different proposed solutions and final evaluation results over the 3 challenge tracks. ...
Acknowledgements We thank all AIM 2020 sponsors: Huawei, MediaTek, NVIDIA, Qualcomm, Google and CVL, ETH Zurich (https://data.vision.ee.ethz.ch/cvl/aim20/). ...
arXiv:2009.12798v1
fatcat:lkc46rz3trak5d277vzern2saq
Real-time single image depth perception in the wild with handheld devices
[article]
2020
arXiv
pre-print
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For the latter, depth estimation from a single image represents the most versatile solution, since a standard camera is available on almost any handheld device. ...
in this paper, we deeply investigate these issues showing how they are both addressable adopting appropriate network design and training strategies -- also outlining how to map the resulting networks on ...
The first application consists of a bokeh filter, aimed at blurring an image according to the distance from the camera. ...
arXiv:2006.05724v1
fatcat:llf5ld6tcnd3fgtqfnetsoh4gq
AIM 2020 Challenge on Image Extreme Inpainting
[article]
2020
arXiv
pre-print
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This paper reviews the AIM 2020 challenge on extreme image inpainting. ...
The challenge had 88 and 74 participants, respectively. 11 and 6 teams competed in the final phase of the challenge, respectively. ...
Acknowledgements We thank the AIM 2020 sponsors: Huawei, MediaTek, Qualcomm AI Research, NVIDIA, Google and Computer Vision Lab / ETH Zürich. ...
arXiv:2010.01110v1
fatcat:sple2mqkkzh2nfz527vqr6c3oi
AIM 2020 Challenge on Video Extreme Super-Resolution: Methods and Results
[article]
2020
arXiv
pre-print
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This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. ...
Track 2 therefore aims at generating visually pleasing results, which are ranked according to human perception, evaluated by a user study. ...
Acknowledgements We thank the AIM 2020 sponsors: Huawei, MediaTek, NVIDIA, Qualcomm, Google, and Computer Vision Lab (CVL), ETH Zurich. ...
arXiv:2009.06290v1
fatcat:bbgfzmwupfgcnigwr2onun4zzm
Portrait Quality Assessment using Multi-Scale CNN
2021
London Imaging Meeting
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To this aim, we create a realistic mannequins database, which contains images from different cameras, shot in several lighting conditions. ...
In this paper, we propose a novel and standardized approach to the problem of camera-quality assessment on portrait scenes. ...
For portrait images, the main focus is to evaluate the render quality of the face. On this matter, characteristics like skin tone, bokeh, texture details and skin smoothness are mostly of interest. ...
doi:10.2352/issn.2694-118x.2021.lim-5
fatcat:n2qvpdfotbhf5dnahla7jj7gpu
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