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Title: :  De-Colorization and Colorization of Video Using GAN and ConvNet.
PaperId: :  14427
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 7 Issue 3 2021
DUI:    16.0415/IJARIIE-14427
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Rishikesh NimbalkarSandip Institute of Technology and Research Centre Nashik
Amit JainSandip Institute of Technology and Research Centre Nashik
Abhijit KshirsagarSandip Institute of Technology and Research Centre Nashik
Mangesh BhandareSandip Institute of Technology and Research Centre Nashik
Prof. Sneha KhaireSandip Institute of Technology and Research Centre Nashik

Abstract

computer engineering
GAN, De-colorization and colorization, pix2pix
Under the limited storage, computing and network bandwidth resources, the video compression coding technology plays an important role for visual communication. To efficiently compress raw video data, a colorization-based video compression coding method is proposed in this work. In the proposed encoder, only the video luminance components are encoded and transmitted. To restore the video chrominance information, a generative adversarial network (GAN) model is adopted in the proposed decoder. To make the GAN work efficiently for video De-colorization and colorization. We investigate GAN as a general-purpose solution to image-to-image translation problems for video. These networks not only learn the mapping from input image to output image, but also learn a loss function to train this mapping. This makes it possible to apply the same generic approach to problems that traditionally would require very different loss formulations. We demonstrate that this approach is effective at synthesizing video frame from label maps, reconstructing objects from edge maps, and colorizing images, among other tasks. Indeed, since the release of the pix2pix software associated with this work, many internet users (many of them artists) have posted their own experiments with our system.

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IJARIIE Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. "De-Colorization and Colorization of Video Using GAN and ConvNet." International Journal Of Advance Research And Innovative Ideas In Education Volume 7 Issue 3 2021 Page 1543-1546
MLA Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. "De-Colorization and Colorization of Video Using GAN and ConvNet.." International Journal Of Advance Research And Innovative Ideas In Education 7.3(2021) : 1543-1546.
APA Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, & Prof. Sneha Khaire. (2021). De-Colorization and Colorization of Video Using GAN and ConvNet.. International Journal Of Advance Research And Innovative Ideas In Education, 7(3), 1543-1546.
Chicago Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. "De-Colorization and Colorization of Video Using GAN and ConvNet.." International Journal Of Advance Research And Innovative Ideas In Education 7, no. 3 (2021) : 1543-1546.
Oxford Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. 'De-Colorization and Colorization of Video Using GAN and ConvNet.', International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, 2021, p. 1543-1546. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/De_Colorization_and_Colorization_of_Video_Using_GAN_and_ConvNet__ijariie14427.pdf (Accessed : 03 December 2023).
Harvard Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. (2021) 'De-Colorization and Colorization of Video Using GAN and ConvNet.', International Journal Of Advance Research And Innovative Ideas In Education, 7(3), pp. 1543-1546IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/De_Colorization_and_Colorization_of_Video_Using_GAN_and_ConvNet__ijariie14427.pdf (Accessed : 03 December 2023)
IEEE Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire, "De-Colorization and Colorization of Video Using GAN and ConvNet.," International Journal Of Advance Research And Innovative Ideas In Education, vol. 7, no. 3, pp. 1543-1546, May-Jun 2021. [Online]. Available: https://ijariie.com/AdminUploadPdf/De_Colorization_and_Colorization_of_Video_Using_GAN_and_ConvNet__ijariie14427.pdf [Accessed : 03 December 2023].
Turabian Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. "De-Colorization and Colorization of Video Using GAN and ConvNet.." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 7 number 3 (03 December 2023).
Vancouver Rishikesh Nimbalkar, Amit Jain, Abhijit Kshirsagar, Mangesh Bhandare, and Prof. Sneha Khaire. De-Colorization and Colorization of Video Using GAN and ConvNet.. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2021 [Cited : 03 December 2023]; 7(3) : 1543-1546. Available from: https://ijariie.com/AdminUploadPdf/De_Colorization_and_Colorization_of_Video_Using_GAN_and_ConvNet__ijariie14427.pdf
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