SRTGAN: Triplet Loss Based Generative Adversarial Network for Real-World Super-Resolution

EasyChair Preprint 7807, version history

Dhruv Patel, Abhinav Jain, Simran Bawkar, Manav Khorasiya, Kalpesh Prajapati, Kishor Upla, Kiran Raja, R. Raghavendra and Christoph Busch

Version	Date	Pages	Version notes
1	April 18, 2022	9
2	October 24, 2022	15	Camera-Ready version of the paper accepted at the Computer Vision and Image Processing Conference (CVIP) 2022. The revised version includes minor changes such as: paper formatted to 15 pages (according to conference format) Acronyms for PSNR, LPIPS, SSIM, etc. are defined. Fig. 2 caption changed to training framework rather than proposed architecture for better understanding. Improved the sentence "The first GAN-based framework called SRGAN [14] introduced.. " such that it was the first to introduce perceptual loss, in addition to using the content and adversarial loss.

Keyphrases: Generative Adversarial Networks, deep learning, image super-resolution

BibTeX entry

BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:

@booklet{EasyChair:7807,
  author    = {Dhruv Patel and Abhinav Jain and Simran Bawkar and Manav Khorasiya and Kalpesh Prajapati and Kishor Upla and Kiran Raja and R. Raghavendra and Christoph Busch},
  title     = {SRTGAN: Triplet Loss Based Generative Adversarial Network for Real-World Super-Resolution},
  howpublished = {EasyChair Preprint 7807},
  year      = {EasyChair, 2022}}