EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring

EQAdap: Equipollent Domain Adaptation Approach to Image Deblurring

In this paper, we present an end-to-end unsupervised domain adaptation approach to image deblurring. This work focuses on learning and generalizing the complex latent space of the source domain and transferring the extracted information to the unlabeled target domain. While fully supervised image de...

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Bibliographic Details
Main Authors: Ibsa Jalata, Naga Venkata Sai Raviteja Chappa, Thanh-Dat Truong, Pierce Helton, Chase Rainwater, Khoa Luu
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep neural networks (DNNs)
instance level affinity-domain adaptation (ILA-DA)
unsupervised domain adaptation (UDA)
Online Access:https://ieeexplore.ieee.org/document/9874820/

Internet

https://ieeexplore.ieee.org/document/9874820/

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