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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.

Sixiang Chen, Tian Ye, Yun Liu, Taodong Liao, Jingxia Jiang, Erkang Chen, Peng Chen• 2022

Related benchmarks

TaskDatasetResultRank
Image DenoisingSIDD
PSNR24.12
124
DesnowingCSD
PSNR33.75
40
Image DesnowingSnow100k
PSNR33.43
34
Multi-task Image RestorationAll-in-One IR Benchmark Average
PSNR31.69
31
DesnowingSRRS
PSNR30.76
28
DerainingAIO-IR Deraining
PSNR28.89
21
DesnowingAIO-IR Desnowing
PSNR32.56
20
DeblurringAIO-IR Deblurring
PSNR27.97
20
Image DesnowingCSD (test)
PSNR33.75
16
Image DehazingAll-in-One IR Benchmark Dehazing
PSNR36.56
15
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