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[ICLR2025] Official Implementations "InterLCM: Low-Quality Images as Intermediate States of Latent Consistency Models for Effective Blind Face Restoration"
[CVPR 2024] SinSR: Diffusion-Based Image Super-Resolution in a Single Step
This is the implementation of several supervised and unsupervised approaches for multiphoton microscopy image denoising, including CARE, DnCNN, ResNet, Noise2Noise, Noise2Void, Probabilistic Noise2…
LAN: Learning to Adapt Noise for Image Denoising (包含了相关数据集、Restormer以及CnDNN模型)的复现
Release for Improved Denoising Diffusion Probabilistic Models
This repository maintains a collection of important papers on conditional image synthesis with diffusion models (Survey Paper published in TMLR2025)
[CVPR 2022] Official implementation of the paper "Uformer: A General U-Shaped Transformer for Image Restoration".
收集 CVPR 最新的成果,包括论文、代码和demo视频等,欢迎大家推荐!Collect the latest CVPR (Conference on Computer Vision and Pattern Recognition) results, including papers, code, and demo videos, etc., and welcome recommendati…
[CVPR 2024] When StyleGAN Meets Stable Diffusion: a W+ Adapter for Personalized Image Generation
Official repository for "Prompting Latent Diffusion for Fast Unpaired Image-to-Image Translation"
Contour-Guided Diffusion Models for Unpaired Image-to-Image Translation
This may be the simplest implement of DDPM. You can directly run Main.py to train the UNet on CIFAR-10 dataset and see the amazing process of denoising.
The state-of-the-art image restoration model without nonlinear activation functions.
Pytorch implementation for codes in Noise Imitation Based Adversarial Training for Robust Multimodal Sentiment Analysis (Accepted by IEEE Transactions on Multimedia).
Many studies have shown that the performance on deep learning is significantly affected by volume of training data. The MedicalNet project provides a series of 3D-ResNet pre-trained models and rela…
Official code repository for the paper: Dehazing Ultrasound using Diffusion Models
Implementation of Denoising Diffusion Probabilistic Model in Pytorch