115 citations · 266 across the 8 of their papers we have counts for
6 papers · 1 filter
Learnability Enhancement for Low-light Raw Denoising: Where Paired Real Data Meets Noise Modeling
Hansen Feng, Lizhi Wang, Yuzhi Wang +1
Low-light raw denoising is an important and valuable task in computational photography where learning-based methods trained with paired real data are mainstream. However, the limit…
Robust Deep Ensemble Method for Real-world Image Denoising
Pengju Liu, Hongzhi Zhang, Jinghui Wang +3
Recently, deep learning-based image denoising methods have achieved promising performance on test data with the same distribution as training set, where various denoising models ba…
NBNet: Noise Basis Learning for Image Denoising with Subspace Projection
Shen Cheng, Yuzhi Wang, Haibin Huang +3
In this paper, we introduce NBNet, a novel framework for image denoising. Unlike previous works, we propose to tackle this challenging problem from a new perspective: noise reducti…
Learning Raw Image Denoising with Bayer Pattern Unification and Bayer Preserving Augmentation
Jiaming Liu, Chi-Hao Wu, Yuzhi Wang +8
In this paper, we present new data pre-processing and augmentation techniques for DNN-based raw image denoising. Compared with traditional RGB image denoising, performing this task…
Balanced Quantization: An Effective and Efficient Approach to Quantized Neural Networks
Shuchang Zhou, Yuzhi Wang, He Wen +2
Quantized Neural Networks (QNNs), which use low bitwidth numbers for representing parameters and performing computations, have been proposed to reduce the computation complexity, s…
EAST: An Efficient and Accurate Scene Text Detector
Xinyu Zhou, Cong Yao, He Wen +4
Previous approaches for scene text detection have already achieved promising performances across various benchmarks. However, they usually fall short when dealing with challenging…