联系方式

固定电话：025-83353672

电子邮箱：lichenghua@airia.cn

招生信息

招生专业：计算机科学与技术、电子信息

招生方向：人工智能

个人简介

李成华，国科大南京学院行业导师，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工作至今。目前主要从事深度学习、图像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，荣获南京市委第十五批科技镇长团优秀团员。

2022.04-至今，中国科学院自动化研究所，副研究员；

2018.07—2022.04，中国科学院自动化研究所，助理研究员；

2014.09—2018.07，中国科学院自动化研究所，模式识别与智能系统，博士。

学术成果

[1] Xiaoran Qin, Yu Zhu,Chenghua Li*, Peisong Wang, Jian Cheng. CIDBNet: A Consecutively-Interactive Dual-Branch Network for JPEG Compressed Image Super-Resolution. Computer Vision–ECCV2022 Workshops: Tel Aviv, Israel, October 23–27, 2022, Proceedings, Part II. Cham: Springer Nature Switzerland, 2023: 458-474.

[2] 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, pp. 1032-1040.

[3]Qian Zheng, Ruipeng Gang, Yuntian Cao, Chenghua Li, Ji Fang, Chenming Liu, Yizhen Cao. A RAW Burst Super-Resolution Method with Enhanced Denoising.PRCV(4) 2022: 103-116.

[4] Zhuolong Jiang, Chengzhi Shen,Chenghua Li*, Hongzhi Liu, Wei Chen. Noise Map Guided Inpainting Network for Low-Light Image Enhancement.PRCV, 2021:201-213.

[5] Zhu Yu, Zhenyu Guo, Tian Liang, Xiangyu He,Chenghua Li*, Cong Leng, Bo Jiang, Yifan Zhang, Jian Cheng. EEDNet: Enhanced Encoder-Decoder Network for AutoISP.ECCVWorkshops, 2020:171-184.

[6] Shuai Liu,Chenghua Li*, Nan Nan, Ziyao Zong, Ruixia Song. MMDM: Multi-frame and Multi-scale for Image Demoiréing.CVPRWorkshops, 2020: 1751-1759.

[7] Chunjie Zhang,Chenghua Li, Jian Cheng. Few-Shot Visual Classification Using Image Pairs With Binary Transformation.TCSVT, 30(9):2867 - 2871, 2020.

[8]Chenghua Li, Qi Kang, Guojing Ge, Qiang Song, Hanqing Lu, Jian Cheng. DeepBE: Learning Deep Binary Encoding for Multi-label Classification.CVPRWorkshops 2016: 744-751.

[9]Chenghua Li, Qiang Song, Yuhang Wang, Hang Song, Qi Kang, Jian Cheng, Hanqing Lu. Learning to recognition from Bing Clickture data.ICMEWorkshops 2016: 1-4.

获奖情况

[1]AIM 2022 Challenge on Reversed ISP（Track 1 S7，Track 2 P20）双赛道亚军；

[2]AIM 2022 Challenge on Defilter（滤镜去除）赛道亚军；

[3]AIM 2022 Challenge on Super-Resolution of Compressed Image季军；

[4]AIM 2020 Challenge on Learned ISP Track 1: Fidelity冠军；

[5]AIM 2020 Challenge on Rendering Realistic Bokeh Track1：CPU和Track 2： smartphone GPU双赛道冠军；

[6]AIM 2020 Challenge on Scene Relighting and Illumination Estimation: Track 2 Illumination Settings Estimation冠军；

[7]AIM 2020 Challenge on Efficient Super-Resolution 亚军；

[8]NTIRE 2020 Challenge on Real Image Denoising: Track 2 sRGB 亚军；

[9]NTIRE 2020 Challenge on Real Image Demoireing Track 1: Single Image季军、Track 2: Burst亚军；

[10]AIM 2019 Challenge on Constrained Super-Resolution Track 1: Parameters亚军及Track2: Inference季军；

[11]2016.04获得MSR图像精细分类竞赛冠军；