MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing
About
Snow removal causes challenges due to its characteristic of complex degradations. To this end, targeted treatment of multi-scale snow degradations is critical for the network to learn effective snow removal. In order to handle the diverse scenes, we propose a multi-scale projection transformer (MSP-Former), which understands and covers a variety of snow degradation features in a multi-path manner, and integrates comprehensive scene context information for clean reconstruction via self-attention operation. For the local details of various snow degradations, the local capture module is introduced in parallel to assist in the rebuilding of a clean image. Such design achieves the SOTA performance on three desnowing benchmark datasets while costing the low parameters and computational complexity, providing a guarantee of practicality.
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Image Denoising | SIDD | PSNR24.12 | 124 | |
| Desnowing | CSD | PSNR33.75 | 40 | |
| Image Desnowing | Snow100k | PSNR33.43 | 34 | |
| Multi-task Image Restoration | All-in-One IR Benchmark Average | PSNR31.69 | 31 | |
| Desnowing | SRRS | PSNR30.76 | 28 | |
| Deraining | AIO-IR Deraining | PSNR28.89 | 21 | |
| Desnowing | AIO-IR Desnowing | PSNR32.56 | 20 | |
| Deblurring | AIO-IR Deblurring | PSNR27.97 | 20 | |
| Image Desnowing | CSD (test) | PSNR33.75 | 16 | |
| Image Dehazing | All-in-One IR Benchmark Dehazing | PSNR36.56 | 15 |