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cs.CV2025
Learning Hazing to Dehazing: Towards Realistic Haze Generation for Real-World Image Dehazing
Ruiyi Wang, Yushuo Zheng, Zicheng Zhang +4
Existing real-world image dehazing methods primarily attempt to fine-tune pre-trained models or adapt their inference procedures, thus heavily relying on the pre-trained models and…
cs.CV2024
HazeCLIP: Towards Language Guided Real-World Image Dehazing
Ruiyi Wang, Wenhao Li, Xiaohong Liu +4
Existing methods have achieved remarkable performance in image dehazing, particularly on synthetic datasets. However, they often struggle with real-world hazy images due to domain…
cs.CV2024★ 1 cited
DehazeDCT: Towards Effective Non-Homogeneous Dehazing via Deformable Convolutional Transformer
Wei Dong, Han Zhou, Ruiyi Wang +3
Image dehazing, a pivotal task in low-level vision, aims to restore the visibility and detail from hazy images. Many deep learning methods with powerful representation learning cap…