GFPGAN-for-Video-SR VS ganspace

Compare GFPGAN-for-Video-SR vs ganspace and see what are their differences.

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GFPGAN-for-Video-SR ganspace
1 3
31 1,766
- -
0.0 0.0
10 months ago over 1 year ago
Jupyter Notebook Jupyter Notebook
- Apache License 2.0
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GFPGAN-for-Video-SR

Posts with mentions or reviews of GFPGAN-for-Video-SR. We have used some of these posts to build our list of alternatives and similar projects.

What are some alternatives?

When comparing GFPGAN-for-Video-SR and ganspace you can also consider the following projects:

nn - 🧑‍🏫 60 Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

pixel2style2pixel - Official Implementation for "Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation" (CVPR 2021) presenting the pixel2style2pixel (pSp) framework

Real-ESRGAN-Video-Batch-Process - Upscale any number of videos using this colab notebook!

ganbert-pytorch - Enhancing the BERT training with Semi-supervised Generative Adversarial Networks in Pytorch/HuggingFace

gan-vae-pretrained-pytorch - Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

ru-dalle - Generate images from texts. In Russian

License-super-resolution - A License Plate Image Reconstruction Project in Tensorflow2

HugsVision - HugsVision is a easy to use huggingface wrapper for state-of-the-art computer vision

Real-ESRGAN-ncnn-vulkan - NCNN implementation of Real-ESRGAN. Real-ESRGAN aims at developing Practical Algorithms for General Image Restoration.

PTI - Official Implementation for "Pivotal Tuning for Latent-based editing of Real Images" (ACM TOG 2022) https://arxiv.org/abs/2106.05744

stylegan-encoder - StyleGAN Encoder - converts real images to latent space

Few-Shot-Patch-Based-Training - The official implementation of our SIGGRAPH 2020 paper Interactive Video Stylization Using Few-Shot Patch-Based Training