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🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
High-Resolution Image Synthesis with Latent Diffusion Models
🤗 Diffusers: State-of-the-art diffusion models for image and audio generation in PyTorch and FLAX.
deep learning for image processing including classification and object-detection etc.
Datasets, Transforms and Models specific to Computer Vision
Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.
Official repo for consistency models.
Practice on cifar100(ResNet, DenseNet, VGG, GoogleNet, InceptionV3, InceptionV4, Inception-ResNetv2, Xception, Resnet In Resnet, ResNext,ShuffleNet, ShuffleNetv2, MobileNet, MobileNetv2, SqueezeNet…
Pytorch implementation of U-Net, R2U-Net, Attention U-Net, and Attention R2U-Net.
Contrastive unpaired image-to-image translation, faster and lighter training than cyclegan (ECCV 2020, in PyTorch)
PyTorch implementation for SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
[ECCV2024] Pixel-Aware Stable Diffusion for Realistic Image Super-Resolution and Personalized Stylization
Tackling the Generative Learning Trilemma with Denoising Diffusion GANs https://arxiv.org/abs/2112.07804
Code for "Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models" [TPAMI 2023]
Contrastive Learning for Compact Single Image Dehazing, CVPR2021
A very simple implementation of cyclegan, which is based on pytorch.
Semantic-Aware Discriminator for Image Super-Resolution
Official PyTorch implementation of AdaDiff described in the paper (https://arxiv.org/abs/2207.05876).
Here is the code for the TPAMI paper: Advancing Real-World Image Dehazing:Perspective, Modules, and Training.
Multi-Organ Foundation Model for Universal Ultrasound Image Segmentation with Task Prompt and Anatomical Prior
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