Search Results for author: Fenglong Song

Found 11 papers, 6 papers with code

Towards Real World HDRTV Reconstruction: A Data Synthesis-based Approach

no code implementations6 Nov 2022 Zhen Cheng, Tao Wang, Yong Li, Fenglong Song, Chang Chen, Zhiwei Xiong

To solve this problem, we propose a learning-based data synthesis approach to learn the properties of real-world SDRTVs by integrating several tone mapping priors into both network structures and loss functions.

Tone Mapping

SJ-HD^2R: Selective Joint High Dynamic Range and Denoising Imaging for Dynamic Scenes

no code implementations20 Jun 2022 Wei Li, Shuai Xiao, Tianhong Dai, Shanxin Yuan, Tao Wang, Cheng Li, Fenglong Song

To further leverage these two paradigms, we propose a selective and joint HDR and denoising (SJ-HD$^2$R) imaging framework, utilizing scenario-specific priors to conduct the path selection with an accuracy of more than 93. 3$\%$.


Real-time Image Enhancer via Learnable Spatial-aware 3D Lookup Tables

no code implementations ICCV 2021 Tao Wang, Yong Li, Jingyang Peng, Yipeng Ma, Xian Wang, Fenglong Song, Youliang Yan

One is a 1D weight vector used for image-level scenario adaptation, the other is a 3D weight map aimed for pixel-wise category fusion.

Image Enhancement

Ultra-High-Definition Image Dehazing via Multi-Guided Bilateral Learning

1 code implementation CVPR 2021 Zhuoran Zheng, Wenqi Ren, Xiaochun Cao, Xiaobin Hu, Tao Wang, Fenglong Song, Xiuyi Jia

To address the problem, we propose a novel network capable of real-time dehazing of 4K images on a single GPU, which consists of three deep CNNs.

Image Dehazing Single Image Dehazing

Multi-Scale Separable Network for Ultra-High-Definition Video Deblurring

1 code implementation ICCV 2021 Senyou Deng, Wenqi Ren, Yanyang Yan, Tao Wang, Fenglong Song, Xiaochun Cao

Although recent research has witnessed a significant progress on the video deblurring task, these methods struggle to reconcile inference efficiency and visual quality simultaneously, especially on ultra-high-definition (UHD) videos (e. g., 4K resolution).


NODE: Extreme Low Light Raw Image Denoising using a Noise Decomposition Network

no code implementations11 Sep 2019 Hao Guan, Liu Liu, Sean Moran, Fenglong Song, Gregory Slabaugh

In this paper, we propose a multi-task deep neural network called Noise Decomposition (NODE) that explicitly and separately estimates defective pixel noise, in conjunction with Gaussian and Poisson noise, to denoise an extreme low light image.

Image Denoising

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