SwinIR
An image super-resolution model based on the Swin Transformer architecture. By incorporating a shifted-window attention mechanism, SwinIR captures long-range pixel dependencies and demonstrates strong performance on image super-resolution and image restoration benchmarks.
Core Facts
Timeline (last 90 days)
Commonly used local super-resolution tools in the community include Real-ESRGAN, SwinIR, 4x-UltraSharp, and others.
SwinIR introduced the Swin Transformer architecture to better capture long-range pixel dependencies.
Deep learning-based super-resolution models such as ESRGAN, Real-ESRGAN, and SwinIR can learn the mapping from low resolution to high resolution, outperforming bicubic interpolation.
OpenModelDB（openmodeldb.info）是一个社区驱动的超分辨率模型数据库，收录了数百个社区训练的超分模型，涵盖 ESRGAN、Real-ESRGAN、SwinIR、HAT、DAT 等架构类型
All Facts (6)
Image Super Resolution uses deep learning models such as Real-ESRGAN and SwinIR to perform intelligent interpolation on low-resolution images, supplementing high-frequency detail information inferred by the AI.
70%UnverifiedImpact-Pack的Upscaler模块支持RealESRGAN、SwinIR等主流超分模型
85%UnverifiedCommonly used local super-resolution tools in the community include Real-ESRGAN, SwinIR, 4x-UltraSharp, and others.
50%UnverifiedSwinIR introduced the Swin Transformer architecture to better capture long-range pixel dependencies.
50%UnverifiedDeep learning-based super-resolution models such as ESRGAN, Real-ESRGAN, and SwinIR can learn the mapping from low resolution to high resolution, outperforming bicubic interpolation.
50%UnverifiedOpenModelDB（openmodeldb.info）是一个社区驱动的超分辨率模型数据库，收录了数百个社区训练的超分模型，涵盖 ESRGAN、Real-ESRGAN、SwinIR、HAT、DAT 等架构类型
50%