Ling-Hao Han

Nankai University — China

Computer Science · Physical Sciences

10h-index1.0kcitations16works0.02yr avg
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Research Topics

Image Enhancement Techniques(6), Advanced Image Processing Techniques(6), Advanced Vision and Imaging(5), Advanced Neural Network Applications(3), Video Surveillance and Tracking Methods(3)

Publications16 total

Lighting Every Darkness in Two Pairs : A Calibration-Free Pipeline for RAW Denoising
2023· 18 cited
Make Explicit Calibration Implicit: Calibrate Denoiser Instead of the Noise Model
arXiv (Cornell University)·2023Open Access
Underwater Ranker: Learn Which Is Better and How to Be Better
Proceedings of the AAAI Conference on Artificial Intelligence·2023· 152 citedOpen Access
DNF: Decouple and Feedback Network for Seeing in the Dark
2023· 52 cited
AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation
2023· 60 cited
AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation
arXiv (Cornell University)·2023· 4 citedOpen Access
Deeply Explain CNN Via Hierarchical Decomposition
International Journal of Computer Vision·2023· 14 cited
Multi-Mode Interactive Image Segmentation
Proceedings of the 30th ACM International Conference on Multimedia·2022· 7 cited
Underwater Ranker: Learn Which Is Better and How to Be Better
arXiv (Cornell University)·2022· 11 citedOpen Access
NTIRE 2022 Challenge on Night Photography Rendering
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)·2022· 40 citedOpen Access
Deeply Explain CNN via Hierarchical Decomposition
arXiv (Cornell University)·2022Open Access
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence·2021· 526 cited
Online Attention Accumulation for Weakly Supervised Semantic Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence·2021· 78 cited
Low-Light Image and Video Enhancement Using Deep Learning: A Survey
arXiv (Cornell University)·2021· 30 citedOpen Access
Lighting the Darkness in the Deep Learning Era.
arXiv (Cornell University)·2021· 5 citedOpen Access
The Moving Target Recognition and Tracking Using RGB-D Data with the Mobile Robot
2019· 3 cited

Frequent Co-authors

Chunle Guo(11), Chongyi Li(9), Ming‐Ming Cheng(8), Chen Change Loy(3), Peng-Tao Jiang(3), Qibin Hou(3), Xin Jin(3), Jun Jiang(2), Jinwei Gu(2), Ruiqi Wu(2), Xin Jin(2), Weidong Zhang(2), Zhi Chai(2), Zhen Li(2), Zuo-Liang Zhu(2), Jia-wen Xiao(2), Ruixun Zhang(2), Xialei Liu(2), Liang Wang(2), Philip H. S. Torr(2)