Vision Transformers for Single Image Dehazing

🤖 Plain-English Summary

Image dehazing is a representative low-level vision task that estimates latent haze-free images from hazy images. We also collect a large-scale realistic remote sensing dehazing dataset for evaluating the method's capability to remove highly non-homogeneous haze.

🔑 Key Findings

• In recent years, convolutional neural network-based methods have dominated image dehazing.
• However, vision Transformers, which has recently made a breakthrough in high-level vision tasks, has not brought new dimensions to image dehazing.
• We start with the popular Swin Transformer and find that several of its key designs are unsuitable for image dehazing.

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