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SEMI-SUPERVISED LEARNING OF CAMERA MOTION FROM A BLURRED IMAGE

Citation Author(s):
Nimisha T M, Vijay Rengarajan, Rajagopalan Ambasamudram
Submitted by:
Nimisha Thekke Madam
Last updated:
6 October 2018 - 8:47am
Document Type:
Presentation Slides
Document Year:
2018
Event:
Presenters:
Subeesh Vasu
Paper Code:
2541
 

We address the problem of camera motion estimation from a single blurred image with the aid of deep convolutional neural networks.
Unlike learning-based prior works that estimate a space-invariant blur kernel, we solve for the global camera motion which in turn
represents the space-variant blur at each pixel. Leveraging the camera motion as well as the clean reference image during training, we resort to a semi-supervised training scheme that utilizes the strengths of both supervised and unsupervised learning to solve for the camera motion undergone by a space-variant blurred image. Finally, we show the effectiveness of such a motion estimation network with applications in space-variant deblurring and change detection.

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