Topic: srgan Goto Github
Some thing interesting about srgan
Some thing interesting about srgan
srgan,A tensorflow-based implementation of SISR using EDSR, SRResNet, and SRGAN
User: ahmad-zaki
srgan,A modern PyTorch implementation of SRGAN
User: aitorzip
Home Page: https://arxiv.org/abs/1609.04802
srgan,A Novel Approach to Video Super-Resolution using Frame Recurrence and Generative Adversarial Networks | Python3 | PyTorch | OpenCV2 | GANs | CNNs
User: amanchadha
Home Page: http://amanchadha.com/projects/ai/dl/AmanChadha_CS230ProjectMilestone.pdf
srgan,iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
User: amanchadha
Home Page: https://arxiv.org/abs/2006.11161
srgan,Generating super-resolution images using GANs
User: apurbasengupta
srgan,Reimplementation of SRGAN using TensorFlow 2
User: arxyzan
srgan,SRCNN_SRGAN_ESRGAN_ON_BRAIN_MRI
User: ashishpatel26
srgan,SRGAN Keras For Medical Images
User: ashishpatel26
srgan,Photo Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras
User: avivsham
srgan,Mozart - A Generative Art Platform
User: bharathraj-v
srgan,A tutorial to super resolution and SRGAN in PyTorch
User: boomb0om
srgan,Tensorflow implementation of the SRGAN algorithm for single image super-resolution
User: brade31919
srgan,🔥 Real-time Super Resolution enhancement (4x) with content loss and relativistic adversarial optimization 🔥
User: braindotai
Home Page: https://arxiv.org/abs/1809.00219
srgan,Research on ESRGAN (Enhanced Super-Resolution Generative Adversarial Networks, published in ECCV 2018), implemented in Tensorflow 2.0. All implementation deployed on Google Colab, and make some modify with origin Architecture include Losses.
User: dang3tion
srgan,Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network implemented in Keras
User: deepak112
srgan,A PyTorch implementation of SRGAN specific for Anime Super Resolution based on "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network". And another PyTorch WGAN-gp implementation of SRGAN referring to "Improved Training of Wasserstein GANs".
User: goldhuang
srgan,A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
User: hasnainraz
srgan,Tensorflow Implementation of enhanced deep super-resolution network (EDSR) and Super Resolution Generative Adversarial Networks(SRGAN) Paper
User: imvision12
srgan,Built and trained SISR GAN models with loss analysis and performance comparison (TF + Keras)
User: jacklu0831
srgan,In this project, I create several Generative Adversatial Network models for various Image to Image translation tasks. The models were first trained using tensorflow. Then, I use Flask to create a web-based implementation for uploading images and getting the augmented image.
User: jain-aayush
srgan,Generative Adversarial Networks with TensorFlow2, Keras and Python (Jupyter Notebooks Implementations)
User: kartikgill
Home Page: https://dropsofai.com
srgan,PyTorch version of the paper: "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
User: kayr7
srgan,Awesome Generative Adversarial Networks with tensorflow
User: kozistr
srgan,Tensorflow 2.x based implementation of EDSR, WDSR and SRGAN for single image super-resolution
User: krasserm
srgan,A PyTorch implementation of SRGAN based on CVPR 2017 paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
User: leftthomas
srgan,A collection of state-of-the-art video or single-image super-resolution architectures, reimplemented in tensorflow.
User: loseall
srgan,Using GANs to interpolate Head Related Transfer Functions
User: madelinehjenkins
srgan,KERAS implementation of the First Multi-Scale Gradient Capsule GAN for Super-Resolution
User: mahdiyarmm
srgan,SRGAN (super resolution generative adversarial networks) with WGAN loss function in TensorFlow
User: mingtaoguo
srgan,Object-Oriented Image Super-Resolution
User: nyuxz
srgan,Applying SRGAN technique implemented in https://github.com/zsdonghao/SRGAN on videos to super resolve them.
User: ravisvi
srgan,Applied Self Supervised Learning techniques such as Jigsaw as pretext task, SRGAN and SimCLR for fine-grained classification
User: rush2406
Home Page: https://arxiv.org/abs/2107.13973
srgan,Generative Adversarial Network for single image super-resolution in high content screening microscopy images
User: saurabh23
srgan,WindSR Dataset contains more than 22,000 pairs of HR/LR wind speed images, which are processed using the NASA's GEOS-5 Nature Run dataset. This dataset is useful for studying super-resolution for data collected using satellites rather natural RGB images.
Organization: sekilab
srgan,Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
User: sgrvinod
srgan,This Repository Contains Solution to the Assignments of the Generative Adversarial Networks (GANs) Specialization from deeplearning.ai on Coursera Taught by Sharon Zhou, Eda Zhou, Eric Zelikman
User: shantanu1109
srgan,collection of super-resolution models & algorithms
User: soapisnotfat
srgan,Official PyTorch implementation of Harmonizing Maximum Likelihood with GANs for Multimodal Conditional Generation (ICLR 2019)
User: soochan-lee
Home Page: https://soochanlee.com/publications/mr-gan
srgan,A Tensorflow2.0 implementation of Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
User: tanyachutani
srgan,Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
Organization: tensorlayer
Home Page: https://github.com/tensorlayer/tensorlayerx
srgan,Tensorflow implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" (Ledig et al. 2017)
User: trevor-m
srgan,An Unofficial PyTorch Implementation for Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
User: twhui
srgan,Various models for handling underexposure, overexposure, super-resolution, shadow removal, etc.
User: wkhademi
srgan,Open Source Image and Video Restoration Toolbox for Super-resolution, Denoise, Deblurring, etc. Currently, it includes EDSR, RCAN, SRResNet, SRGAN, ESRGAN, EDVR, BasicVSR, SwinIR, ECBSR, etc. Also support StyleGAN2, DFDNet.
Organization: xpixelgroup
Home Page: https://basicsr.readthedocs.io/en/latest/
srgan,Image Super-Resolution Using SRCNN, DRRN, SRGAN, CGAN in Pytorch
User: yiyang7
srgan,PyTorch implementation of the paper "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network"
User: zijundeng
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