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We aim to generate high resolution shallow depth-of-field (DoF) images from a single all-in-focus image with controllable focal distance and aperture size.
The accumulation buffer: hardware support for high-quality rendering
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Depth from focus with your mobile phone. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 3497–3506
Supasorn Suwajanakorn, Carlos Hernandez, and Steven M Seitz. 2015 · 2015
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High-quality depth from uncalibrated small motion clip. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 5413–5421
Hyowon Ha, Sunghoon Im, Jaesik Park, Hae-Gon Jeon, and In So Kweon. 2016 · 2016
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Deep residual learning for image recognition. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 770–778
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016 · 2016
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Deeper depth prediction with fully convolutional residual networks. In 3D Vision, 2016 Fourth International Conference on . IEEE, 239–248
Iro Laina, Christian Rupprecht, Vasileios Belagiannis, Federico Tombari, and Nassir Navab. 2016 · 2016
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Pyramid scene parsing network. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition . 2881–2890
Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, and Jiaya Jia. 2017 · 2017
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MegaDepth: Learning Single-View Depth Prediction from Internet Photos. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
Zhengqi Li and Noah Snavely. 2018 · 2018
Closest in time.
Aperture Supervision for Monocular Depth Estimation. In Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
Pratul P. Srinivasan, Rahul Garg, Neal Wadhwa, Ren Ng, and Jonathan T. Barron. 2018 · 2018
Closest in time.