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Blur kernel estimation by deep learning

Full Thesis Title: 
Blur kernel estimation by deep learning
Supervisor: 
Tak Ming Wong
Thesis Type: 
Status: 
In Progress
Student: 
Manuel Jüngst
Short Description: 
Recently, computer vision community developed several motion deblurring and single image super-resolution methods, which model the deblurring process by deep neural network. However, estimating an explicit blur kernel still plays an important role in image processing perspective. The aim of this work is to study in blur kernel estimation on conventional RGB image using state-of-arts deep learning technique.
Start Date: 
Thursday, February 6, 2020