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Deep Salient Video Deblurring (Dsvd) Framework
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Deblurring has been a major challenge in image restoration tasks. Video deblurring poses a new set of challenges as compared to image deblurring due to dimensionality as well as information connected in frames. GAN has been quite successful in the image deblurring tasks, taking inspiration from this we have proposed Deep Salient Video Deblurring (DSVD) Framework using GAN. Saliency features help reduce the area of focus in the frames while guiding the GAN through the training phase. We have used VideoDeblurring and GOPRO datasets to test our model and compared it to the various techniques we've discussed. In terms of Peak Signal-to-Noise Ratio (PSNR), our approach performs better than others. It particularly does well on heavily noised video frames. The results have been optimistic.
Title: Deep Salient Video Deblurring (Dsvd) Framework
Description:
Deblurring has been a major challenge in image restoration tasks.
Video deblurring poses a new set of challenges as compared to image deblurring due to dimensionality as well as information connected in frames.
GAN has been quite successful in the image deblurring tasks, taking inspiration from this we have proposed Deep Salient Video Deblurring (DSVD) Framework using GAN.
Saliency features help reduce the area of focus in the frames while guiding the GAN through the training phase.
We have used VideoDeblurring and GOPRO datasets to test our model and compared it to the various techniques we've discussed.
In terms of Peak Signal-to-Noise Ratio (PSNR), our approach performs better than others.
It particularly does well on heavily noised video frames.
The results have been optimistic.
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