1 code implementation • 9 Mar 2024 • Chunwei Tian, Menghua Zheng, Tiancai Jiao, WangMeng Zuo, Yanning Zhang, Chia-Wen Lin
Popular convolutional neural networks mainly use paired images in a supervised way for image watermark removal.
1 code implementation • 4 Mar 2024 • Chunwei Tian, Menghua Zheng, Bo Li, Yanning Zhang, Shichao Zhang, David Zhang
Specifically, mentioned paired watermark images are obtained in a self supervised way, and paired noisy images (i. e., noisy and reference images) are obtained in a supervised way.
1 code implementation • 16 Oct 2023 • Chunwei Tian, Menghua Zheng, WangMeng Zuo, Shichao Zhang, Yanning Zhang, Chia-Wen Ling
To avoid loss of key information, PB uses three heterogeneous networks to implement multiple interactions of multi-level features to broadly search for extra information for improving the adaptability of an obtained denoiser for complex scenes.
1 code implementation • 26 Sep 2022 • Chunwei Tian, Menghua Zheng, WangMeng Zuo, Bob Zhang, Yanning Zhang, David Zhang
In this paper, we propose a multi-stage image denoising CNN with the wavelet transform (MWDCNN) via three stages, i. e., a dynamic convolutional block (DCB), two cascaded wavelet transform and enhancement blocks (WEBs) and a residual block (RB).