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Source code of "Balancing Efficiency and Restoration: Lightweight Mamba-Based Model for CT Metal Artifact Reduction"
FIND-Net (Fourier-Integrated Network with Dictionary Kernels) is a deep learning model for Metal Artifact Reduction (MAR) in CT imaging. It integrates Fast Fourier Convolution (FFC) and trainable G…
This is the official PyTorch implementation of DehazeDCT. Our method achieves the second best performance in NTIRE 2024 Dense and NonHomogeneous Dehazing Challenge (CVPR workshop))
Heterogeneous window Transformer for image denoising (IEEE TSMC,2024)
A Light-weight and Multi-scale Network for Medical Image Segmentation
[ECCV 2024] Histoformer: Restoring Images in Adverse Weather Conditions via Histogram Transformer
Learning An Effective Transformer for Remote Sensing Satellite Image Dehazing
Vision Transformers for Single Image Dehazing
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SUNet: Swin Transformer with UNet for Image Denoising
Official implementation of DenoMamba: A fused state-space model for low-dose CT denoising
From Heavy Rain Removal to Detail Restoration: A Faster and Better Network
U-shaped Vision Mamba for Single Image Dehazing
⏰ Agenticly track worldwide conference deadlines (Website, Python Cli, Wechat Applet)
Multi-scale Attention Network for Single Image Super-Resolution (CVPRW 2024)
Dual residual attention network for image denoising (Pattern Recognition, 2024)
This is official implementtaion of "VmambaIR: Visual State Space Model for Image Restoration"
(ACM TOMM) This is the official code repository for "VM-UNet: Vision Mamba UNet for Medical Image Segmentation".
Pytorch implementation of "LightM-UNet: Mamba Assists in Lightweight UNet for Medical Image Segmentation"
[MICCAI 2024] All-In-One Medical Image Restoration via Task-Adaptive Routing (AMIR).
Plug-and-Play Image Restoration with Deep Denoiser Prior (IEEE TPAMI 2021) (PyTorch)
SwinIR: Image Restoration Using Swin Transformer (official repository)