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 Desnowing | CSD (test) | PSNR33.75 | 16 | |
| Desnowing | Image Restoration Desnowing | PSNR32.81 | 13 | |
| All-in-one Image Restoration | Combined (Deraining, Desnowing, Dehazing) | PSNR31.65 | 13 | |
| Dehazing | Image Restoration Dehazing | PSNR32.89 | 13 | |
| Deraining | Deraining | PSNR29.25 | 13 | |
| Image Desnowing | SRRS (test) | PSNR30.76 | 6 | |
| Image Desnowing | Snow100K (test) | PSNR33.43 | 6 |