I am a Ph.D. candidate in Computer Science at University of Rochester, advised by Prof. Jiebo Luo. Before that, I received the B.Sc. and the M.Sc. degrees from the University of Science and Technology of China, respectively advised by Prof. Lu Fang. My research interests include computer vision and machine learning.
Advisor: Jiebo Luo
Advisor: Lu Fang
Thesis: Semantic Segmentation via Generative Model.
Thesis: Automatic Stylistic Painting Transferring.
H. Zheng, Z. Lin, J. Lu, S. Cohen, J. Zhang, N. Xu, J. Luo, “Semantic Layout Manipulation with High-Resolution Sparse Attention,” (under review), 2020. [arXiv]
H. Zheng, H. Liao, L, Chen, W. Xiong, T. Chen, J. Luo, “Example-Guided Image Synthesis across Arbitrary Scenes using Masked Spatial-Channel Attention and Self-Supervision,” in Proc. of the European Conference on Computer Vision (ECCV), 2020. [arXiv] [code] [project page]
Y. Tan*, H. Zheng*, Y. Zhu, X. Yuan, X. Lin, D. Brady, L. Fang, “CrossNet++: Cross-scale Large-parallax Warping for Reference-based Super-resolution,” IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020.
T. Chen, W. Xiong, H. Zheng, J. Luo, “Image Sentiment Transfer, in Proc. of the ACM Multimedia (ACMMM), 2020.2018
H. Zheng, M. Ji, H, Wang, Y. Liu, L. Fang, “CrossNet: An End-to-end Reference-based Super Resolution Network using Cross-scale Warping,” in Proc. of the European Conference on Computer Vision (ECCV), 2018. [arXiv] [code]2017
H. Zheng, M. Ji, Z. Xu, H, Wang, Y. Liu, L. Fang, “Learning Cross-scale Correspondence and Patchbased Synthesis for Reference-based Super-Resolution,” in Proc. of the British Machine Vision Conference (BMVC), 2017. [paper]
M. Ji, G. Juergen, H. Zheng, Y. Liu, L. Fang, “SurfaceNet: an End-to-end 3D Neural Network for Multiview Stereopsis,” in Proc. of the International Conference on Computer Vision (ICCV), 2017. [arXiv] [code]
H. Zheng, M. Guo, Y. Liu, L. Fang, “Combining Exemplar-based Approach and learning-based Approach for Light Field Super-resolution Using a Hybrid Imaging System,” in Proc. of The International Conference on Computer Vision workshop (ICCV workshop), 2017. [paper]2016
H. Zheng, L. Fang, M. Ji, M. Strese, Y. Oezer, E. Steinbach, “Deep Learning for Surface Material Classification Using Haptic and Visual Information,” IEEE Transactions on Multimedia (TMM), 2016, Vol. 18, pp. 2407-2416. [arXiv] [code]
Y. Zhou, T. Thanh, H. Zheng, L. Fang, N. M. Cheung, “Computation and Memory Efficient Image Segmentation,” IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2016.2015
H. Zheng, L. Fang, M. Ji, “Learning High-level Prior with Convolutional Neural Networks for Semantic Segmentation,”, 2016. [arXiv]
H. Zheng, G. Cheung, L. Fang , “Analysis of Sports Statistics via Graph-Signal Smoothness Prior,” in Proc. of Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA-ASC), 2015.
M. Ji, L. Fang, H. Zheng, M. Strese, E.Steinbach, “Preprocessing-free Surface Material Classification Using Convolutional Neural Networks Pretrained by Sparse Autoencoder (ACNN),” in Proc. of Machine Learning for Signal Processing (MLSP), 2015.2014
T. T. Do, Y. Zhou, H. Zheng, N. M. Cheung, D. Koh , “Early melanoma diagnosis with mobile imaging,” in Proc. of The 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2014.2013
T. T. Do, Y. Zhou, H. Zheng, H. Nejati, N.M. Cheung, et al., “Design of a Mobile Imaging System for Early Diagnosis of Skin Cancer,” in Proc. of IEEE Life Sciences Grand Challenges Conference, 2013, Best Poster Award.