Vision Transformers for Single Image Dehazing

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.

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

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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