AIFNet
PI: Miu Ling Lam
AIFNet is a deep neural network for removing spatially-varying defocus blur from a single defocused image. We leverage light field synthetic aperture and refocusing techniques to generate a large set of realistic defocused and all-in-focus image pairs depicting a variety of natural scenes for network training. AIFNet consists of three modules: defocus map estimation, deblurring and domain adaptation. The effects and performance of various network components are extensively evaluated. We also compare our method with existing solutions using several publicly available datasets. Quantitative and qualitative evaluations demonstrate that AIFNet shows the state-of-the-art performance.
For more information about the project, please visit:
https://sweb.cityu.edu.hk/miullam/AIFNET/