High-fidelity performance metrics for generative models in PyTorch
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Updated
Jan 25, 2024 - Python
High-fidelity performance metrics for generative models in PyTorch
PyTorch - FID calculation with proper image resizing and quantization steps [CVPR 2022]
Pytorch implementation of common image generation metrics.
IS, FID score Pytorch and TF implementation, TF implementation is a wrapper of the official ones.
[CVPR 2024] On the Content Bias in Fréchet Video Distance
Pytorch implementation of Visual DNA, an approach to represent and compare images.
Frechet Inception Distance for Keras-based GANs
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
A pip-installable evaluator for GANs (IS and FID). Accepts either dataloaders or individual batches. Supports on-the-fly evaluation during training. A working DCGAN SVHN demo script provided.
Official Repository for the paper "Feature Extraction for Generative Medical Imaging Evaluation: New Evidence Against an Evolving Trend".
Lots of evaluation metrics for the generative adversarial networks in pytorch
CXR-ACGAN: Auxiliary Classifier GAN (AC-GAN) for Chest X-Ray (CXR) Images Generation (Pneumonia, COVID-19 and healthy patients) for the purpose of data augmentation. Implemented in TensorFlow, trained on COVIDx CXR-3 dataset.
PyTorch implementation of 'DDPM' (Ho et al., 2020) and training it on CelebA 64×64
PyTorch implementation of WGAN-GP-based video generation. Includes functionality for measuring Frechet Video Distance and implementing recent research improvements of WGAN-GP. Read paper at https://github.com/talcron/frame-prediction-pytorch/blob/media/paper.pdf
Computing the Sliding Fréchet Inception Distance between fake and real images with continous labels
The FID-Evaluator is a tool to analyze how the FID behaves when the embedding space is reduced.
Implementation of GAN-based text-to-image models for a comparative study on the CUB and COCO datasets
Capturing the special characteristics of Claude Monet's paintings in order to turn ordinary pictures into similar style paintings
GAN-based framework to generate depth images of infants from a desired image and pose
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