5 papers
HNDiff: Haze-Noise Diffusion for Image Dehazing
Jin-Ting He, Fu-Jen Tsai, Yan-Tsung Peng +3
Existing diffusion-based methods have recently made significant progress in image dehazing. However, they typically neglect the physics of haze formation and reconstruct clean imag…
DDTNet: Degradation Disentanglement and Transfer Network for Test-Time All-in-One De-weathering Adaptation
Kuan-Hung Lin, Fu-Jen Tsai, Yan-Tsung Peng +3
All-in-one adverse weather image restoration aims to remove multiple degradations, such as rain, haze, and snow, using a single unified model. Despite their broad applicability, ex…
BlurDM: A Blur Diffusion Model for Image Deblurring
Jin-Ting He, Fu-Jen Tsai, Yan-Tsung Peng +3
Diffusion models show promise for dynamic scene deblurring; however, existing studies often fail to leverage the intrinsic nature of the blurring process within diffusion models, l…
PHATNet: A Physics-guided Haze Transfer Network for Domain-adaptive Real-world Image Dehazing
Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin +1
Image dehazing aims to remove unwanted hazy artifacts in images. Although previous research has collected paired real-world hazy and haze-free images to improve dehazing models' pe…
TANet: Triplet Attention Network for All-In-One Adverse Weather Image Restoration
Hsing-Hua Wang, Fu-Jen Tsai, Yen-Yu Lin +1
Adverse weather image restoration aims to remove unwanted degraded artifacts, such as haze, rain, and snow, caused by adverse weather conditions. Existing methods achieve remarkabl…