super-resolution
Fast-SRGAN
| super-resolution | Fast-SRGAN | |
|---|---|---|
| 2 | - | |
| 1,452 | 638 | |
| - | - | |
| 0.0 | 0.0 | |
| almost 2 years ago | about 2 months ago | |
| Python | Python | |
| Apache License 2.0 | MIT License |
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super-resolution
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Is it not possible to get good results in Deep Learning if dataset is small (1000 images)? [D]
https://github.com/krasserm/super-resolution (Super useful for me)
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How to train "models" for opensv edsr (iam super noob)
And thanks ! so it means that I need to train it with one of these trainers inside this project for example https://github.com/krasserm/super-resolution And that means that iam forced to use python (at least for training) but it's OK 🙃
Fast-SRGAN
We haven't tracked posts mentioning Fast-SRGAN yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
MIRNet-TFJS - TensorFlow JS models for MIRNet for low-light💡 image enhancement
a-PyTorch-Tutorial-to-Super-Resolution - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network | a PyTorch Tutorial to Super-Resolution
TrainYourOwnYOLO - Train a state-of-the-art yolov3 object detector from scratch!
awesome-colab-notebooks - Collection of google colaboratory notebooks for fast and easy experiments
SRGAN - Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network
iSeeBetter - 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
Hands-On-Meta-Learning-With-Python - Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
CleanTF2plus - Clean TF2's sequel
License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2
EDSR_Tensorflow - TensorFlow implementation of 'Enhanced Deep Residual Networks for Single Image Super-Resolution'.
SinGAN - Official pytorch implementation of the paper: "SinGAN: Learning a Generative Model from a Single Natural Image"
EGVSR - Efficient & Generic Video Super-Resolution