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Snow removal causes challenges due to its characteristic of complexdegradations. To this end, targeted treatment of multi-scale snow degradationsis critical for the network to learn effective snow removal. In order to handlethe diverse scenes, we propose a multi-scale projection transformer(MSP-Former), which understands and covers a variety of snow degradationfeatures in a multi-path manner, and integrates comprehensive scene contextinformation for clean reconstruction via self-attention operation. For thelocal details of various snow degradations, the local capture module isintroduced in parallel to assist in the rebuilding of a clean image. Suchdesign achieves the SOTA performance on three desnowing benchmark datasetswhile costing the low parameters and computational complexity, providing aguarantee of practicality.

MSP-Former: Multi-Scale Projection Transformer for Single Image Desnowing