20 citations · 23 across the 2 of their papers we have counts for
2 papers
cs.CV2022★ 3 cited
Semi-UFormer: Semi-supervised Uncertainty-aware Transformer for Image Dehazing
Ming Tong, Yongzhen Wang, Peng Cui +2
Image dehazing is fundamental yet not well-solved in computer vision. Most cutting-edge models are trained in synthetic data, leading to the poor performance on real-world hazy sce…
cs.CV2022★ 20 cited
UCL-Dehaze: Towards Real-world Image Dehazing via Unsupervised Contrastive Learning
Yongzhen Wang, Xuefeng Yan, Fu Lee Wang +4
While the wisdom of training an image dehazing model on synthetic hazy data can alleviate the difficulty of collecting real-world hazy/clean image pairs, it brings the well-known d…