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D2BGAN: A Dark to Bright Image Conversion Model for . . . - IEEE Xplore This paper presents an image enhancement model, D2BGAN (Dark to Bright Generative Adversarial Network), to translate low light images to bright images without a paired supervision We introduce the use of geometric and lighting consistency along with a contextual loss criterion
PyTorch Implementation of paper titled D2BGAN: A Dark to . . . - GitHub D2BGAN is a CycleGAN model that is designed to convert low light images to bright images It is an unpaired GAN-based image enhancement operation that uses cycle consistency, geometric consistency, and illumination consistency
Image Processing Laboratory - Dark to Bright Image Conversion We cooperate with Prof Jhilik Bhattacharya (Thapar University, India) in the development of an image enhancement model named D2BGAN (Dark to Bright Generative Adversarial Network) to translate low light images to bright images without a paired supervision
D2BGAN | Sasika Amarasinghe D2BGAN is a CycleGAN model that is designed to convert low light images to bright images It is an unpaired GAN-based image enhancement operation that uses cycle consistency, geometric consistency, and illumination consistency