35 citations · 220 across the 36 of their papers we have counts for
4 papers · 1 filter
IDR: Self-Supervised Image Denoising via Iterative Data Refinement
Yi Zhang, Dasong Li, Ka Lung Law +3
The lack of large-scale noisy-clean image pairs restricts supervised denoising methods' deployment in actual applications. While existing unsupervised methods are able to learn ima…
Rethinking Noise Synthesis and Modeling in Raw Denoising
Yi Zhang, Hongwei Qin, Xiaogang Wang +1
The lack of large-scale real raw image denoising dataset gives rise to challenges on synthesizing realistic raw image noise for training denoising models. However, the real raw ima…
HLIC: Harmonizing Optimization Metrics in Learned Image Compression by Reinforcement Learning
Baocheng Sun, Meng Gu, Dailan He +3
Learned image compression is making good progress in recent years. Peak signal-to-noise ratio (PSNR) and multi-scale structural similarity (MS-SSIM) are the two most popular evalua…
Checkerboard Context Model for Efficient Learned Image Compression
Dailan He, Yaoyan Zheng, Baocheng Sun +2
For learned image compression, the autoregressive context model is proved effective in improving the rate-distortion (RD) performance. Because it helps remove spatial redundancies…