[MICCAI 2025] TAT: Task-Adaptive Transformer for All-in-One Medical Image Restoration

[IEEE TIP 2024] TTST: A Top-k Token Selective Transformer for Remote Sensing Image Super-Resolution

[IEEE TMM 2024] Frequency-Assisted Mamba for Remote Sensing Image Super-Resolution

[TIP 2026] "FourierSR: A Fourier Token-based Plugin for Efficient Image Super-Resolution"

List of awesome infrared small targets detection methods!

Official code for the TGRS 2024 paper "SCINet: Spatial and Contrast Interactive Super-Resolution Assisted Infrared UAV Target Detection"

Official dataset and code of Continuous Optical Zooming: A Benchmark for Arbitrary-Scale Image Super-Resolution in Real World[CVPR2024].

CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped, CVPR 2022

Lightweight single-image super-resolution based on RWKV

Lightweight Single Image Super-Resolution with Non-Causal Linear Attention and Frequency-Aware Modeling

IHRFNet: Integrating Residual and Hybrid Attention Blocks with Feature Extraction Network for Image Denoising

visualization：filter、feature map、attention map、image-mask、grad-cam、human keypoint、guided-backpro

[IJCV 2025] Unaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance

Pytorch implementation of paper, "Enhancing Lightweight Image Super-Resolution through Frequency-Enhanced Mamba Networks"

Spikingformer: A Key Foundation Model for Spiking Neural Networks (AAAI 2026)

Kolmogorov-Arnold Attention: Is Learnable Attention Better for Vision Transformers?

MoH: Multi-Head Attention as Mixture-of-Head Attention

QDM: Quadtree-Based Region-Adaptive Sparse Diffusion Models for Efficient Image Super-Resolution

A paper list of spiking neural networks, including papers, codes, and related websites. 本仓库收集脉冲神经网络相关的顶会顶刊以及CNS论文和代码，正在持续更新中。

Adapt or Perish: Adaptive Sparse Transformer with Attentive Feature Refinement for Image Restoration

Preception Consistency Ultarsound Images Super-resolution via Self-supervised CycleGAN

[CVPR 2025] Complexity Experts are Task-Discriminative Learners for Any Image Restoration

models and codes for Multi-scale strip-shaped convolution attention network for lightweight image super-resolution (MSAN)

PyTorch codes for "Heterogeneous Mixture of Experts for Remote Sensing Image Super-Resolution", IEEE GRSL, 2025.

Hierarchical mixture of sparse attention for remote sensing image super-resolution

[AAAI 2026] "Seeing Through the Rain: Resolving High-Frequency Conflicts in Deraining and Super-Resolution via Diffusion Guidance"

Official PyTorch implementation of The Linear Attention Resurrection in Vision Transformer