个人简介 :

李成华，中国科学院自动化研究所副研究员，2018年在中国科学院自动化研究所博士毕业，并留所工作至今。目前主要从事深度学习、图像与视频内容分析方面研究，在图像视频增强领域获得国际著名竞赛NTIRE、AIM冠亚季军10余项，发表学术论文10余篇，申请发明专利20余项。现为中国图象图形学会会员、CSIG视觉大数据专委会委员，荣获南京市省第十五批科技镇长团优秀团员。

发表论文 :

[1] Chenghua, Li; Qiang, Song; Yuhang, Wang; Hang, Song; Qi, Kang; Jian, Cheng; Hanqing, Lu ; Learning to recognition from Bing Clickture data, 2016 IEEE International Conference on Multimedia \& Expo Workshops, Seattle, WA, USA, 2016-7-11至2016-7-15.

[2] Shuai, Liu; Chenghua, Li; Nan, Nan; Ziyao, Zong; Ruixia, Song ; MMDM: Multi-frame and Multi-scale for Image Demoiréing, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), Seattle, WA, USA, 2020-6-14至2020-6-19.

[3] Zhang, Chunjie; Li, Chenghua; Cheng, Jian ; Few-Shot Visual Classification Using Image Pairs With Binary Transformation, IEEE Transactions on Circuits and Systems for Video Technology, 2019, 30(9): 2867-2871.

[4] Xiaoran Qin; Yu Zhu; Chenghua Li; Peisong Wang; Jian Cheng ; CIDBNet: A Consecutively-Interactive Dual-Branch Network for JPEG Compressed Image Super-Resolution, ECCV 2022: Computer Vision – ECCV 2022 Workshops, Tel Aviv, Israel, 2022-8-23至2022-8-27.

[5] Fangya Li; Ruipeng Gang; Chenghua Li; Jinjing Li; Sai Ma; Chenming Liu; Yizhen Cao ; Gamma-Enhanced Spatial Attention Network for Efficient High Dynamic Range Imaging, Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2022, New Orleans Ernest N. Morial Convention Center, 2022-6-19至2022-6-20.

获奖情况 :

AIM 2020 Challenge on Rendering Realistic Bokeh Track1: CPU,Track 2: Smartphone GPU 双赛道冠军；
AIM 2020 Challenge on Learned ISP Track 1: Fidelity冠军；
AIM 2020 Challenge on Scene Relighting and Illumination Estimation: Track 2 Illumination Settings Estimation冠军；
AIM 2022 Challenge on Reversed ISP（Track 1 S7，Track 2 P20）双赛道亚军;
AIM 2022 Challenge on Instagram Filter Removal亚军;
AIM 2022 Challenge on Super-Resolution of Compressed Image季军;
AIM 2020 Challenge on Efficient Super-Resolution 亚军；
NTIRE 2020 Challenge on Real Image Denoising: Track 2 sRGB 亚军；
NTIRE 2020 Challenge on Real Image Demoireing Track 1: Single Image季军、Track 2: Burst亚军；
AIM 2019 Challenge on Constrained Super-Resolution Track 1: Parameters亚军及Track2: Inference季军。