Jing Huo (霍静)   Associate Professor (准聘副教授) R&L Group Department of Computer Science and Technology, , Nanjing, China Address: Room 901, Department of Computer Science and Technology No. 163 Xianlin Avenue Nanjing, Jiangsu, China, 210023 Email: [email protected]; [email protected]

Biography

Currently I am an Associate Professor of the Department of Computer Science and Technology in and a member of R&L Group, led by professor Yang Gao.
I received my B.Eng. degree in in June 2011 from .
I received my Ph.D. degree in the Department of Computer Science and Technology in June 2017 from .
I visited from September 2015 to September 2016, under the supervision of .
I visited The University of Hong Kong in August and October, 2018, working with and .

Research Interests

Research interests include machine learning and computer vision.
Particularly in embodied AI, diffusion model, generative adversarial learning and their application to image and video generation, robotics, etc.

Positions

• 招收博士后、助理研究员及工程师（视频图像生成、具身智能等方向）等，全年有效，欢迎与我联系!
  
• 
  

Publications

• 
  
• Jing Huo, Xiangde Liu, Wenbin Li, Yang Gao, Hujun Yin, Jiebo Luo.
  CAST: Learning both Geometric and Texture Style Transfers for Effective Caricature Generation.
  IEEE Transactions on Image Processing (TIP) , 2022.
• Meihao Kong, Jing Huo*, Wenbin Li, Jing Wu, Yu-Kun Lai, Yang Gao
  Playing Lottery Tickets in Style Transfer Models.
  ACM MM Workshop , 2022.
• Wenbin Li, Lei Wang, Xingxing Zhang, Lei Qi, Jing Huo, Yang Gao, Jiebo Luo
  Defensive Few-shot Learning.
  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI) , 2022.
• Wenbin Li, Yanfang Liu, Jing Huo, Yinghuan Shi, Yang Gao, Lei Wang, Jiebo Luo
  A Multilayer Framework for Online Metric Learning.
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS) , 2022.
• Jing Huo, Shiyin Jin, Wenbin Li, Jing Wu, Yu-Kun Lai, Yinghuan Shi, Yang Gao.
  Manifold Alignment for Semantically Aligned Style Transfer.
  Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) , 2021, Oral, 14861-14869.
• Haodi Hou, Jing Huo*, Jing Wu, Yu-Kun Lai and Yang Gao.
  MW-GAN: Multi-Warping GAN for Caricature Generation With Multi-Style Geometric Exaggeration.
  IEEE Transactions on Image Processing (IEEE TIP), vol. 30, pp. 8644-8657, 2021.
• Zheng Gu, Wenbin Li, Jing Huo*, Lei Wang, Yang Gao.
  LoFGAN: Fusing Local Representations for Few-Shot Image Generation.
  Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), 2021, 8463-8471.
• Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Xin Geng, Yang Gao.
  Adversarial Camera Alignment Network for Unsupervised Cross-camera Person Re-identification
  IEEE Transactions on Circuits and Systems for Video Technology, 2021.
• Zheng Gu, Chuanqi Dong, Jing Huo*, Wenbin Li, Yang Gao.
  CariMe: Unpaired Caricature Generation with Multiple Exaggerations.
  IEEE Transactions on Multimedia, 2021.
• Hongwei Huang, Zhangkai Wu, Wenbin Li*, Jing Huo*, Yang Gao.
  Local descriptor-based multi-prototype network for few-shot Learning.
  Pattern Recognition, 2021.
• Li Yang, Jing Wu, Jing Huo*, Yu-Kun Lai, Yang Gao.
  Learning 3D Face Reconstruction from a Single Sketch.
  Graphical Models, 2021.
• Wenbin Li, Wei Xiong, Haofu Liao, Jing Huo, Yang Gao, Jiebo Luo.
  
  Neural Networks, 2020.
• Wen Ji, Kelei He*, Jing Huo*, Zheng Gu, Yang Gao.
  Unsupervised Domain Attention Adaptation Network for Caricature Attribute Recognition.
  European Conference on Computer Vision (ECCV), 2020.
• Chuanqi Dong, Wenbin Li, Jing Huo*, Zheng Gu, Yang Gao.
  Learning Task-aware Local Representations for Few-Shot Learning.
  International Joint Conference on Artificial Intelligence (IJCAI), 2020.
• Wenbin Li, Lei Wang, Jing Huo*, YinghuanShi ,Yang Gao, Jiebo Luo.
  Asymmetric Distribution Measure for Few-shot Learning.
  International Joint Conference on Artificial Intelligence (IJCAI), 2020.
• Changbin Shao, Jing Huo*, Lei Qi,Zhen-Hua Feng, Wenbin Li, Chuanqi Dong,Yang Gao.
  Biased Feature Learning for Occlusion Invariant Face Recognition.
  International Joint Conference on Artificial Intelligence (IJCAI), 2020.
• Lei Qi, Lei Wang, Jing Huo, Yinghuan Shi, Yang Gao.
  Progressive Cross-camera Soft-label Learning for Semi-supervised Person Re-identification.
  IEEE Trans. on Circuits and Systems for Video Technology (TCSVT), 2020
• HaodiHou, Jing Huo, Yang Gao.
  Cross-Domain Adversarial Autoencoder for Fine Grained Category Preserving Image Translation.
  IJCNN, 2020.
• Xiao Liu, Wenbin Li, Jing Huo, Lili Yao, Yang Gao.
  Layerwise Sparse Coding for Pruned Deep Neural Networks with Extreme Compression Ratio.
  AAAI Conference on Artificial Intelligence (AAAI), 2020.
• Chuanqi Dong, Zheng Gu, Zhonghao Huang, Wen Ji, Jing Huo, Yang Gao.
  DeepMEF: A Deep Model Ensemble Framework for Video Based Multi-modal Person Identification.
  ACM Multimedia, Grand Challenge, 2019. (3rd place)
• Jianrong Chen, Li Yang, Yuanyuan Xu, Jing Huo, Yinghuan Shi, Yang Gao.
  A Novel Deep Multi-Modal Feature Fusion Method for Celebrity Video Identification.
  ACM Multimedia, Grand Challenge, 2019. (5th place)
• Lei Qi, Lei Wang, Jing Huo, Luping Zhou, Yinghuan Shi and Yang Gao.
  A Novel Unsupervised Camera-aware Domain Adaptation Framework for Person Re-identification.
  IEEE International Conference on Computer Vision (ICCV), 2019.
• Wenbin Li, Lei Wang, Jinglin Xu, Jing Huo, Yang Gao and Jiebo Luo.
  Revisiting Local Descriptor based Image-to-Class Measure for Few-shot Learning.
  IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2019.
• Wenbin Li, Jinglin Xu, Jing Huo, Lei Wang, Yang Gao, Jiebo Luo.
  Distribution Consistency based Covariance Metric Networks for Few-shot Learning.
  AAAI Conference on Artificial Intelligence (AAAI), 2019.
• Lei Qi, Jing Huo, Lei Wang, Yinghuan Shi, Yang Gao
  
  IEEE International Conference on Multimedia and Expo (ICME), 2019.
• Wenbin Li, Jing Huo, Yinghuan Shi, Yang Gao, Lei Wang, Jiebo Luo.
  A Joint Local and Global Deep Metric Learning Method for Caricature Recognition.
  Asian Conference on Computer Vision (ACCV), 2018.
• Lei Qi, Jing Huo, Xiaocong Fan, Yinghuan Shi, Yang Gao.
  
  IEEE Journal of Selected Topics in Signal Processing (IJSTSP), 2018, 12(6), 1263-1275.
• Jing Huo, Wenbin Li, Yinghuan Shi, Yang Gao, Hujun Yin.
  
  British Machine Vision Conference (BMVC), 2018.
• Jing Huo, Yang Gao, Yinghuan Shi, Hujun Yin.
  
  IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2017, doi: 10.1109/TNNLS.2017.2769128.
• Jing Huo, Yang Gao, Yinghuan Shi, Hujun Yin.
  
  ACM Multimedia Thematic Workshops (ACM MM Workshop), 2017: 340-348.
• Jing Huo, Yang Gao, Yinghuan Shi, Wanqi Yang, Hujun Yin.
  
  IEEE Transactions on Cybernetics (TCYB), 2018, 48(6), 1814-1826.
• Jing Huo, Yang Gao, Yinghuan Shi, Wanqi Yang, Hujun Yin.
  
  ACM Conference on Multimedia (ACM MM), 2016: 1405-1414. (Full Paper)
• Jing Huo, Yang Gao, Wanqi Yang, Hujun Yin.
  
  International Journal of Neural Systems (IJNS), 2014, 24(3).
• Jing Huo, Yang Gao, Wanqi Yang, Hujun Yin.
  
  Intelligent Data Engineering and Automated Learning (IDEAL), 2012, pp. 76–83. (Best Paper Award).
• Wenbin Li, Yang Gao, Lei Wang, Luping Zhou, Jing Huo, Yinghuan Shi.
  
  Pattern Recognition (PR), 2018, 75, 302-314.
• Yusheng Jia, Yang Gao, Wanqi Yang, Jing Huo, Yinghuan Shi.
  A Novel Ego-centered Academic Community Detection Approach via Factor Graph Model.
  Intelligent Data Engineering and Automated Learning (IDEAL), 2014, pp. 223-230, (2014).
• 何克磊, 史颖欢, 高阳, 霍静, 汪栋, 张缨.
  
  计算机学报, 2016, 40(6), pp. 1265-1274.
• 于谦, 高阳, 霍静, 庄韫恺.
  
  软件学报, 2015, 26(11): 2897-2911.
• 俞亚君, 霍静, 史颖欢, 高阳, 张剡.
  
  星际娱乐城 学报（自然科学版）, 2013, 49(005): pp. 611-618.
• 张媛媛, 霍静, 杨琬琪, 高阳, 史颖欢.
  
  智能系统学报, 2015(02): pp. 193-200.

Awards and Honors

• 2022 国家级青年人才项目
• 2020 华为杯第二届中国研究生人工智能创新大赛一等奖，优秀指导教师
• 2018 江苏省科学技术奖二等奖
• 2018 江苏省计算机学会优秀博士学位论文
• 2017 Nanjing University Outstanding Graduation Student

Demo

• Results of Video Style Transfer

Datasets

NJU-ID Dataset Nanjing University ID Card Face (NJU-ID) Dataset is developed for research on ID card face verification. It includes face images of 256 persons. For each person, there are one low resolution ID card face image and one high resolution face image captured by a digital camera.

WebCaricature Dataset WebCaricature dataset is developed for caricature recognition. It is a large photograph-caricature dataset consisting of 6042 caricatures and 5974 photographs from 252 persons collected from the web.

WebCariA Dataset Face attribute data for images in WebCaricature. 50 intrinsic face attributes are labeled for each image.