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Paper References

[1] Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
[2] DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Better
[3] Towards Robust Monocular Depth Estimation: Mixing Datasets for Zero-shot Cross-dataset Transfer
[4] BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
[5] MaskGAN: Towards Diverse and Interactive Facial Image Manipulation
[6] Real-Time User-Guided Image Colorization with Learned Deep Priors
[7] Rethinking Atrous Convolution for Semantic Image Segmentation
[8] Deep Image Matting
[9] AOD-Net: All-In-One Dehazing Network
[10] When AWGN-based Denoiser Meets Real Noises
[11] EnlightenGAN: Deep Light Enhancement without Paired Supervision
[12] RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
[13] Deep Two-Stage High-Resolution Image Inpainting

Code References

The following have been ported :
[1] https://github.com/switchablenorms/CelebAMask-HQ
[2] https://github.com/TAMU-VITA/DeblurGANv2
[3] https://github.com/zllrunning/face-parsing.PyTorch
[4] https://github.com/junyanz/interactive-deep-colorization
[5] https://github.com/intel-isl/MiDaS
[6] https://github.com/twtygqyy/pytorch-SRResNet
[7] https://github.com/huochaitiantang/pytorch-deep-image-matting
[8] https://github.com/MayankSingal/PyTorch-Image-Dehazing
[9] https://github.com/yzhouas/PD-Denoising-pytorch
[10] https://github.com/VITA-Group/EnlightenGAN
[11] https://github.com/hzwer/arXiv2020-RIFE
[12] https://github.com/a-mos/High_Resolution_Image_Inpainting