Search Results for author: Michael Krainin

Found 6 papers, 2 papers with code

Face Deblurring using Dual Camera Fusion on Mobile Phones

no code implementations23 Jul 2022 Wei-Sheng Lai, YiChang Shih, Lun-Cheng Chu, Xiaotong Wu, Sung-Fang Tsai, Michael Krainin, Deqing Sun, Chia-Kai Liang

To the best of our knowledge, our work is the first mobile solution for face motion deblurring that works reliably and robustly over thousands of images in diverse motion and lighting conditions.

Deblurring Image Deblurring +1

SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting

no code implementations ICCV 2021 Varun Jampani, Huiwen Chang, Kyle Sargent, Abhishek Kar, Richard Tucker, Michael Krainin, Dominik Kaeser, William T. Freeman, David Salesin, Brian Curless, Ce Liu

We present SLIDE, a modular and unified system for single image 3D photography that uses a simple yet effective soft layering strategy to better preserve appearance details in novel views.

Image Matting

AutoFlow: Learning a Better Training Set for Optical Flow

1 code implementation CVPR 2021 Deqing Sun, Daniel Vlasic, Charles Herrmann, Varun Jampani, Michael Krainin, Huiwen Chang, Ramin Zabih, William T. Freeman, Ce Liu

Synthetic datasets play a critical role in pre-training CNN models for optical flow, but they are painstaking to generate and hard to adapt to new applications.

Optical Flow Estimation

Robust image stitching with multiple registrations

no code implementations ECCV 2018 Charles Herrmann, Chen Wang, Richard Strong Bowen, Emil Keyder, Michael Krainin, Ce Liu, Ramin Zabih

Here, we observe that the use of a single registration often leads to errors, especially in scenes with significant depth variation or object motion.

Image Stitching

Handheld Multi-Frame Super-Resolution

3 code implementations8 May 2019 Bartlomiej Wronski, Ignacio Garcia-Dorado, Manfred Ernst, Damien Kelly, Michael Krainin, Chia-Kai Liang, Marc Levoy, Peyman Milanfar

In this paper, we supplant the use of traditional demosaicing in single-frame and burst photography pipelines with a multiframe super-resolution algorithm that creates a complete RGB image directly from a burst of CFA raw images.

Demosaicking Multi-Frame Super-Resolution

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