Hao Dong

董豪 北京大学 助理教授 博士生导师 博雅青年学者 智源学者

hao.dong@pku.edu.cn

Google Scholar / Github: Person / Lab


About Me

I am an Assistant Professor at Peking University, where I lead Hyperplane Lab. My research interests include embodied AI, robotics and computer vision. My current research focuses on several exciting areas: robot vision, generalizable robotic manipulation, and autonomous decision making. The ultimate goal is to create cost-effective and autonomous robots for both industrial applications and home assistance scenarios. Additionally, I am fortunate to serve as an Area Chair (AC) or Senior Program Committee (SPC) member for CVPR, NeurIPS and AAAI conferences, and as the Associate Editor (AE) of ICRA and Machine Intelligence Research.

I lead several open source projects, such as TensorLayer and OpenMLsys, and have won the Best Open Source Software Award at ACM Multimedia, as well as the OpenI Outstanding Project Award twice.

Before joining PKU, I obtained my Ph.D. degree from Imperial College London under the supervision of Yike Guo. Prior to my Ph.D., I received a MSc specialist degree (visual information processing) with distinction from Imperial, and a first-class BEng degree from the University of Central Lancashire. Furthermore, I have founded a startup focused on AI-driven brain-computer interface with Yike Guo between 2012 and 2015.

News

  • [2023/09] NEW Five papers get accepted to NeurIPS 2023
  • [2023/09] NEW I will serve as an associate editor of ICRA
  • [2023/08] One paper gets accepted to SIGGRAPH Asia, and two papers for BMVC
  • [2023/07] Two papers get accepted to ICCV 2023
  • [2023/06] I will serve as an AC of CVPR 2024
  • [2023/06] I will serve as a SPC of AAAI 2024
  • show more
  • [2023/04] Our visual-audio navigation paper gets accepted to RAL
  • [2023/03] I will serve as an AC of NeurIPS 2023
  • [2023/02] Three paper get accepted to CVPR 2023
  • [2023/02] Our TensorLayerX won the OpenI Outstanding Open Source Project Award 2022
  • [2023/01] Three papers get accepted to ICRA, ICLR and AAAI respectively
  • [2022/12] We won the Dual Object Manipulation Track of MyoChallenge @ NeurIPS 2022
  • [2022/11] Our metasurface indoor robotic paradigm gets accepted to National Science Review
  • [2022/10] I will serve as a co-chair of Learning Robot Manipulation Forum @ PRCV 2022
  • [2022/09] Two papers get accepted to NeurIPS 2022
  • [2022/09] I will serve as an AC of CVPR 2023
  • [2022/07] I will serve as a SPC of AAAI 2023
  • [2022/07] Two papers get accepted to ECCV 2022
  • [2022/07] I will serve as a co-chair for Human in the Loop Learning (HiLL) Workshop @ NeurIPS 2022
  • [2022/06] I serve as an associate editor of Machine Intelligence Research
  • [2022/06] One paper gets accepted to IROS 2022
  • [2022/05] Our open-source ML system book is released @ OpenMLsys
  • Hyperplane Lab

    Our lab, affiliated with the CFCS and the School of CS at PKU, is currently welcoming interns, masters, PhD and postdocs to join our research on embodied AI. Our lab's name, 'Hyperplane Lab', reflects our commitment to exploring diverse and evolving frontiers in AI and robotics, allowing our research to adapt and grow as the field evolves.

    I also have the leading of the Embodied AI center at the Beijing Academy of Artificial Intelligence (BAAI 北京智源), where we are actively seeking for research scientists, engineers, and interns. Additionally, I am also honored to be a member of PengCheng Lab (PCL 鹏城实验室), where I contribute to a variety of exciting open-source projects.
    lab members
    PhD Students
    Ruihai Wu 2020
    Mingdong Wu 2021
    Tianhao Wu 2021
    Yan Zhao 2022
    Hongcheng Wang 2022
    Jiyao Zhang 2023
    Xiaoqi Li 2023
    Yuxing Long 2024
    Yuanfei Wang 2024
    MSc Students
    Taewhan Kim 2022
    Zichen Zhang 2023
    Fei Hu 2023
    Hisham Barakat 2023
    Yaroslav Ponomarenko 2023
    Former Interns
    Guanqi Zhan BS@PKU -> PhD@Oxford Mingxin Yu BS@PKU -> PhD@MIT Junning Shao BS@PKU -> PhD@THU Zihan Ding MSc@Imperial -> PhD@Princeton
    Jiahao Huang BS@BIT -> PhD@Imperial Jialei Huang BS@PKU -> PhD@THU Haoqi Yuan BS@PKU -> PhD@PKU Andrew Zhao BS@UBC -> PhD@THU
    Yihao Zhao BS@PKU -> PhD@PKU Bingchan Zhao BS@PKU -> PhD@PKU Lan Lyu BS@PKU -> MSc@CMU Minghang Zheng BS@PKU -> PhD@PKU
    Zizheng Guo BS@PKU -> PhD@PKU Jie Ren BS@XDU -> PhD@Edin.
    招收校内外实习生 (gap year, 研究生等),对博后、RA和外地访问学生提供充足补贴

    Courses

  • Foundamentals of AI (Spring Term 2023)
  • Introduction to Computing (A) (Fall Term 2022 - 2023)
  • previous courses
  • Deep Generative Models (Spring Term 2020 - 2022)
  • Introduction to Computing (B) (Fall Term 2020 - 2021)
  • Study and Practice on Topics of Frontier Computing (I) (Autumn Term 2019)
  • Introduction to Deep Learning (Turing Class) (Summer Term 2019)

  • Services

  • Area Chair: NeurIPS (2023), CVPR (2023, 2024)
  • Senior Program Committee: AAAI (2023, 2024)
  • Open-Source Organisation: Founder and Organiser of TensorLayer and OpenMLsys communities
  • Associate Editor: ICRA, Machine Intelligence Research

  • Books
    Deep Reinforcement Learning: Fundamentals, Research and Applications
    Hao Dong, Zihan Ding, Shanghang Zhang Eds.
    Springer Nature 2020 ISBN 978-981-15-4094-3
    Other Versions 深度强化学习:基础、研究与应用 董豪、丁子涵、仉尚航 等著(简体中文译本 Simplified Chinese)
    电子工业出版社 2021 ISBN 978-7-121-41188-5
    新一代AI霸主 - 深度強化學習 董豪、丁子涵、仉尚航 等著(繁體中文譯本 Traditional Chinese)
    深智數位 2022 ISBN 978-986-0776-82-9
    [Homepage(及免费中文在线)] [Springer] [Broadview] [繁体版本] [京东]
    Machine Learning System: Design and Implementation
    Luo Mai, Hao Dong Eds. Springer Nature 2023 ISBN coming soon.
    机器学习系统:设计与实现 麦络、董豪 等著
    清华大学出版社 Tsinghua University Press 2023 ISBN 978-7-302-63007-4
    [OpenMLsys Organisation] [免费中文在线] [京东]
    深度学习:一起玩转TensorLayer(Deep Learning using TensorLayer)
    Hao Dong, Yike Guo, Guang Yang et al
    电子工业出版社 Publishing House of Electronics Industry 2018 ISBN: 9787121326226
    [Amazon] [京东] [Broadview] [Code] [Organisation] [Documentation]
    Chapter: Survey on Feature Extraction and Applications of Biosignals
    Akara Supratak, Chao Wu, Hao Dong, Kai Sun, Yike Guo
    Machine Learning for Health Informatics, Springer, Page 161-182 2016
    [Springer]
    [ show more ]
    Papers
    ( show recent selected / show all )
    Discuss Before Moving: Visual Language Navigation via Multi-expert Discussions
    Yuxing Long, Xiaoqi Li, Wenzhe Cai, Hao Dong
    arXiv 2023
    [Paper]
    Bridging Zero-shot Object Navigation and Foundation Models through Pixel-guided Navigation Skill
    Wenzhe Cai, Siyuan Huang, Guangran Cheng, Yuxing Long, Peng Gao, Changyin Sun, Hao Dong
    arXiv 2023
    [Paper] [Code]
    Instruct2Act: Mapping Multi-modality Instructions to Robotic Actions with Large Language Model
    Siyuan Huang, Zhengkai Jiang, Hao Dong, Yu Qiao, Peng Gao, Hongsheng Li
    arXiv 2023
    [Paper] [Code]
    Plan4MC: Skill Reinforcement Learning and Planning for Open-World Minecraft Tasks
    Haoqi Yuan, Chi Zhang, Hongcheng Wang, Feiyang Xie, Penglin Cai, Hao Dong, Zongqing Lu
    arXiv 2023
    [Paper] [Project] [Code]
    Find What You Want: Learning Demand-conditioned Object Attribute Space for Demand-driven Navigation
    ---The First Demand-driven Navigation Paper
    Hongcheng Wang, Andy Guan Hong Chen, Xiaoqi Li, Mingdong Wu, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2023
    [Paper] [Code]
    GenPose: Generative Category-level Object Pose Estimation via Diffusion Models
    Jiyao Zhang, Mingdong Wu, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2023
    [Paper] [Project] [Code]
    Learning Environment-aware Affordance for 3D Articulated Object Manipulation under Occlusions
    Ruihai Wu, Kai Cheng, Yan Zhao, Chuanruo Ning, Guanqi Zhan, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2023
    [Paper] [Code]
    GraspGF: Learning Score-based Grasping Primitive for Human-assisting Dexterous Grasping
    Tianhao Wu, Mingdong Wu, Jiyao Zhang, Yunchong Gan, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2023
    [Paper] [Project] [Code]
    Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objects
    Chuanruo Ning, Ruihai Wu, Haoran Lu, Kaichun Mo, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2023
    [Paper] [Code]
    PerSAM: Personalize Segment Anything Model with One Shot
    Renrui Zhang, Zhengkai Jiang, Ziyu Guo, Shilin Yan, Junting Pan, Hao Dong, Peng Gao, Hongsheng Li
    arXiv 2023
    [Paper] [Code]
    Mixup-Augmented Meta-Learning for Sample-Efficient Fine-Tuning of Protein Simulators
    Jingbang Chen, Yian Wang, Xingwei Qu, Shuangjia Zheng, Yaodong Yang, Hao Dong, Jie Fu
    arXiv 2023
    [Paper] [Code]
    Learning Gradient Fields for Scalable and Generalizable Irregular Packing
    Tianyang Xue, Mingdong Wu, Lin Lu, Haoxuan Wang, Hao Dong, Baoquan Chen
    SIGGRAPH Asia 2023
    [Paper] [Code]
    Learning Part Motion of Articulated Objects Using Spatially Continuous Neural Implicit Representations
    Yushi Du, Ruihai Wu, Yan Shen, Hao Dong
    British Machine Vision Conference (BMVC) 2023
    [Paper] [Project] [Code]
    Score-PA: Score-based 3D Part Assembly
    Junfeng Cheng, Mingdong Wu, Ruiyuan Zhang, Guanqi Zhan, Chao Wu, Hao Dong
    British Machine Vision Conference (BMVC) 2023 (Oral)
    [Paper] [Code]
    MARLlib: A Scalable and Efficient Library For Multi-agent Reinforcement Learning
    Siyi Hu, Yifan Zhong, Minquan Gao, Weixun Wang, Hao Dong, Zhihui Li, Xiaodan Liang, Xiaojun Chang, Yaodong Yang
    Journal of Machine Learning Research (JMLR) 2023
    [Paper] [Documentation] [Code]
    DefoAfford: Learning Foresightful Dense Visual Affordance for Deformable Object Manipulation
    Ruihai Wu, Chuanruo Ning, Hao Dong
    International Conference on Computer Vision (ICCV) 2023
    [Paper] [Project] [Code]
    Leveraging SE(3) Equivariance for Learning 3D Geometric Shape Assembly
    Ruihai Wu, Chenrui Tie, Yushi Du, Yan Zhao, Hao Dong
    International Conference on Computer Vision (ICCV) 2023
    [Paper] [Project] [Code]
    Learning a Universal Human Prior for Dexterous Manipulation from Human Preference
    Zihan Ding, Yuanpei Chen, Allen Z. Ren, Shixiang Shane Gu, Hao Dong, Chi Jin
    RSS Workshop on Learning Dexterous Manipulation 2023
    [Paper]
    Learning Semantic-Agnostic and Spatial-Aware Representation for Generalizable Visual-Audio Navigation
    Hongcheng Wang, Yuxuan Wang, Fangwei Zhong, Mingdong Wu, Jianwei Zhang, Yizhou Wang, Hao Dong
    IEEE Robotics and Automation Letters (RAL) 2023
    [Paper] [Project] [Code]
    SGTAPose: Robot Structure Prior Guided Temporal Attention for Camera-to-Robot Pose Estimation from Image Sequence
    Yang Tian, Jiyao Zhang, Zekai Yin, Hao Dong
    Conference on Computer Vision and Pattern Recognition (CVPR) 2023
    [Paper] [Project]
    GFPose: Learning Gradient Field for Multi-Hypothesis 3D Human Pose Estimation
    Hai Ci, Mingdong Wu, Wentao Zhu, Xiaoxuan Ma, Hao Dong, Fangwei Zhong, Yizhou Wang
    Conference on Computer Vision and Pattern Recognition (CVPR) 2023
    [Paper] [Project] [Code]
    PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observations
    Haoran Geng, Ziming Li, Yiran Geng, Jiayi Chen, Hao Dong, He Wang
    Conference on Computer Vision and Pattern Recognition (CVPR) 2023
    [Paper] [Project] [Code]
    ReBNN: Resilient Binary Neural Network
    Sheng Xu, Yanjing Li, Teli Ma, Mingbao Lin, Hao Dong, Baochang Zhang, Peng Gao, Jinhu Lu
    AAAI Conference on Artificial Intelligence 2023 (Oral)
    [Paper] [Code]
    RLAfford: End-to-End Affordance Learning for Robotic Manipulation
    Yiran Geng, Boshi An, Haoran Geng, Yuanpei Chen, Yaodong Yang, Hao Dong
    International Conference on Robotics and Automation (ICRA) 2023
    [Paper] [Project] [Code]
    DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Object Manipulation
    Yan Zhao, Ruihai Wu, Zhehuan Chen, Yourong Zhang, Qingnan Fan, Kaichun Mo, Hao Dong
    International Conference on Learning Representations (ICLR) 2023
    [Paper] [Project] [Code]
    Object-Centric Masked Image Modeling-Based Self-Supervised Pretraining for Remote Sensing Object Detection
    Tong Zhang, Yin Zhuang, He Chen, Liang Chen, Guanqun Wang, Peng Gao, Hao Dong
    IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2023
    [Paper]
    P2FEViT: Plug-and-Play CNN Feature Embedded Hybrid Vision Transformer for Remote Sensing Image Classification
    Guanqun Wang, He Chen, Liang Chen, Yin Zhuang, Shanghang Zhang, Tong Zhang, Hao Dong, Peng Gao
    Remote Sensing 2023
    [Paper] [Code]
    Intelligent Indoor Metasurface Robotics
    ---Journal Cover Paper: A New Robot Concept for God's Eye View and Privacy
    Hanting Zhao, Shengguo Hu, Hongrui Zhang, Zhuo Wang, Hao Dong, Philipp del Hougne, Tie Jun Cui, Lianlin Li
    National Science Review (NSR) 2022
    [Paper] [Journal Cover]
    Heterogeneous-Agent Mirror Learning: A Continuum of Solutions to Cooperative MARL
    Jakub Grudzien Kuba, Xidong Feng, Shiyao Ding, Hao Dong, Jun Wang, Yaodong Yang
    arXiv 2022
    [Paper] [Code]
    GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning
    Tianhao Wu, Fangwei Zhong, Yiran Geng, Hongchen Wang, Yongjian Zhu, Yizhou Wang, Hao Dong
    arXiv 2022
    [Paper]
    RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environment
    Mingxin Yu*, Lin Shao*, Zhehuan Chen, Tianhao Wu, Qingnan Fan, Kaichun Mo, Hao Dong
    arXiv 2022
    [Paper] [Project]
    TarGF: Learning Target Gradient Field for Object Rearrangement
    Mingdong Wu, Fangwei Zhong, Yulong Xia, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2022
    [Paper] [Project] [Code]
    Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning
    Yuanpei Chen, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuang Jiang, Stephen Marcus McAleer, Hao Dong, Zongqing Lu, Song-Chun Zhu, Yaodong Yang
    Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks 2022
    [Paper] [Project] [Code]
    AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions
    Yian Wang*, Ruihai Wu*, Kaichun Mo*, Jiaqi Ke, Qingnan Fan, Leonidas Guibas, Hao Dong
    European Conference on Computer Vision (ECCV) 2022
    [Paper] [Project] [Code]
    DREDS: Domain Randomization-Enhanced Depth Simulation and Restoration for Perceiving and Grasping Specular and Transparent Objects
    Qiyu Dai*, Jiyao Zhang*, Qiwei Li, Tianhao Wu, Hao Dong, Ziyuan Liu, Ping Tan, He Wang
    European Conference on Computer Vision (ECCV) 2022
    [Paper] [Project] [Code]
    Scalable Model-based Policy Optimization for Decentralized Networked Systems
    Yali Du, Chengdong Ma, Yuchen Liu, Runji Lin, Hao Dong, Jun Wang, Yaodong Yang
    International Conference on Intelligent Robots and Systems (IROS) 2022
    [Paper] [Code]
    VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D Articulated Objects
    Ruihai Wu, Yan Zhao, Kaichun Mo, Zizheng Guo, Yian Wang, Tianhao Wu, Qingnan Fan, Xuelin Chen, Leonidas Guibas, Hao Dong
    International Conference on Learning Representations (ICLR) 2022
    [Paper] [Code] [Project] [Youtube] [Bilibili]
    Consecutive Pre-Training: A Knowledge Transfer Learning Strategy with Relevant Unlabeled Data for Remote Sensing Domain
    Tong Zhang, Peng Gao, Hao Dong, Yin Zhuang, Guanqun Wang, Wei Zhang, He Chen
    Remote Sensing 2022
    [Paper] [Code]
    Hierarchical Disentangling Network for Building Extraction from Very High Resolution Optical Remote Sensing Imagery
    Jianhao Li, Yin Zhuang, Shan Dong, Peng Gao, Hao Dong, He Chen, Liang Chen, Lianlin Li
    Remote Sensing 2022
    [Paper] [Code]
    Adaptive Local Context Embedding for Small Vehicle Detection from Aerial Optical Remote Sensing Images
    Shanjunyu Liu, Yin Zhuang, Hao Dong, Peng Gao, Guanqun Wang, Tong Zhang, Liang Chen, He Chen, Lianlin Li
    IEEE International Geoscience and Remote Sensing Symposium (IGRASS) 2022
    [Paper]
    DMotion: Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos
    ---The First Attempt to Learn the Forward Model Unsupervisedly via Motion Disentanglement
    Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong
    International Conference on Intelligent Robots and Systems (IROS) 2021
    [Paper] [Project] [Code]
    End-to-End Object Detection with Adaptive Clustering Transformer
    Minghang Zheng, Peng Gao, Xiaogang Wang, Hongsheng Li, Hao Dong
    British Machine Vision Conference (BMVC) 2021 (Oral)
    [Paper] [Code]
    Contrastive Multimodal Fusion with TupleInfoNCE
    Yunze Liu, Qingnan Fan, Shanghang Zhang, Hao Dong, Thomas Funkhouser, Li Yi
    International Conference on Computer Vision (ICCV) 2021
    [Paper] [Code]
    P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding
    Yunze Liu, Li Yi, Shanghang Zhang, Qingnan Fan, Thomas Funkhouser, Hao Dong
    arXiv 2012.13089
    [Paper] [Code]
    Tensorlayer 3.0: A Deep Learning Library Compatible with Multiple Backends
    Cheng Lai, Jiarong Han, Hao Dong
    International Conference on Multimedia & Expo Workshops (ICMEW) 2021
    Fast and Flexible Human Pose Estimation with HyperPose
    Yixiao Guo*, Jialei Liu*, Guo Li*, Luo Mai, Hao Dong
    ACM Multimedia (MM) Open Source 2021
    [Paper] [Code]
    Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification
    Chu-ran Wang*, Jing Li*, Fandong Zhang, Xinwei Sun􏰀, Hao Dong, Yizhou Yu, and Yizhou Wang
    IEEE Trans. Image Processing (TIP) 2021
    [Paper]
    Efficient Reinforcement Learning Development with RLzoo
    Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Luo Mai, Hao Dong
    ACM Multimedia (MM) Open Source 2021
    [Paper] [Code]
    Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information
    Jiahao Huang, Weiping Ding, Jun Lv, Jingwen Yang, Hao Dong, Javier Del Ser, Jun Xia, Tiaojuan Ren, Stephen Wong, Guang Yang
    Applied Intelligence 2021
    [Paper]
    Generative 3D Part Assembly via Dynamic Graph Learning
    ---The First Attempt to Assemble 3D Part without External Guidance
    Jialei Huang*, Guanqi Zhan*, Qingnan Fan, Kaichun Mo, Lin Shao, Baoquan Chen, Leonidas Guibas, Hao Dong
    Neural Information Processing Systems (NeurIPS) 2020
    [Paper] [Code] [Project] ( [机器之心]/ [AI科技评论] )
    ACL-GAN: Unpaired Image-to-Image Translation using Adversarial Consistency Loss
    Yihao Zhao, Ruihai Wu, Hao Dong
    European Conference on Computer Vision (ECCV) 2020
    [Paper] [Code] [Project]
    Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control
    Qingrui Zhang, Hao Dong and Wei Pan
    International Conference on Distributed Artificial Intelligence (DAI) 2020 (Oral)
    [Paper]
    Role-Wise Data Augmentation for Knowledge Distillation
    Jie Fu, Xue Geng, Zhijian Duan, Bohan Zhuang, Xingdi Yuan, Adam Trischler, Jie Lin, Chris Pal, Hao Dong
    arXiv-2004.08861 2020
    [Paper] [Code]
    DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation
    Guanqi Zhan, Yihao Zhao, Bingchan Zhao, Haoqi Yuan, Baoquan Chen, Hao Dong
    arXiv:1911.09943 2019
    [Paper]
    An Artificial Intelligence Based Data-driven Approach for Design Ideation
    Liuqing Chen, Pan Wang, Hao Dong, Feng Shi, Ji Han, Yike Guo, Peter RN Childs, Jun Xiao, Chao Wu
    Journal of Visual Communication and Image Representation 2019
    [Paper]
    SIMGAN: Photo-Realistic Semantic Image Manipulation Using Generative Adversarial Networks
    Simiao Yu, Hao Dong, Felix Liang, Yuanhan Mo, Chao Wu, Yike Guo
    International Conference on Image Processing (ICIP) 2019 (Oral)
    [Paper]
    Conditional Image Synthesis Using Stacked Auxiliary Classifier Generative Adversarial Networks
    Zhongwei Yao, Hao Dong, Pan Wang, Chao Wu, Yike Guo
    Future of Information and Communications Conference (FICC) 2018
    [Paper]
    Generative Creativity: Adversarial Learning for Bionic Design
    Simiao Yu, Hao Dong, Pan Wang, Chao Wu, Yike Guo
    International Conference on Artificial Neural Networks (ICANN) Munich, Germany, 2019
    [Paper]
    Text-to-Image Synthesis via Visual-Memory Creative Adversarial Network
    Shengyu Zhang, Hao Dong, Wei Hu, Yike Guo, Chao Wu, Di Xie, Fei Wu
    Pacific Rim Conference on Multimedia (PCM) 2018
    [Paper]
    Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security
    Hao Dong, Chao Wu, Wei Zhen, Yike Guo
    IEEE Trans. on Inform. Forensics and Security (TIFS) 2018
    [Paper]
    Towards Desynchronisation Detection in Biosignals
    Akara Supratak, Steffen Schneider, Hao Dong, Ling Li, Yike Guo
    Neural Inform. Process. Systems (NeurIPS) Time Series Workshop 2017
    [Paper] [Project]
    SisGAN: Semantic Image Synthesis via Adversarial Learning
    ---The First Attempt to Manipulate Image using Natural Language (Text-Guided Image Manipulation)
    Hao Dong*, Simiao Yu*, Chao Wu, Yike Guo
    International Conference on Computer Vision (ICCV) 2017
    [Paper]
    TensorLayer: A Versatile Library for Efficient Deep Learning Development
    ---Winner of the Best Open Source Software Award
    Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo
    ACM Multimedia (MM) Open Source 2017
    [Paper] [Code] [Organisation] [Documentation]
    DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction
    Guang Yang*, Simiao Yu*, Hao Dong, Greg Slabaugh, Pier Luigi Dragotti, Xujiong Ye, Fangde Liu, Simon Arridge, Jennifer Keegan, Yike Guo, David Firmin
    IEEE Trans. Med. Imag. (TMI) 2017
    [Paper] [Code]
    Deep De-Aliasing for Fast Compressive Sensing MRI
    Simiao Yu*, Hao Dong*, Guang Yang, Greg Slabaugh, Pier Luigi Dragotti, Xujiong Ye, Fangde Liu, Simon Arridge, Jennifer Keegan, David Firmin, Yike Guo
    arXiv:1705.07137 2017
    [Paper]
    I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation
    Hao Dong, Jingqing Zhang, Douglas McIlwraith, Yike Guo
    International Conference on Image Processing (ICIP) 2017 (Oral)
    [Paper] [Code]
    Unsupervised Image-to-Image Translation with Generative Adversarial Networks
    Hao Dong, Paarth Neekhara, Chao Wu, Yike Guo
    arXiv:1701.02676 2017
    [Paper] [Code]
    DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG
    Akara Supratak, Hao Dong, Chao Wu, Yike Guo
    IEEE Trans. on Neural Systems and Rehabilitation Eng. (TNSRE) 2017
    [Paper] [Code]
    Mixed Neural Network Approach for Temporal Sleep Stage Classification
    Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M Matthews, Yike Guo
    IEEE Trans. on Neural Systems and Rehabilitation Eng. (TNSRE) 2017
    [Paper]
    Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks
    Hao Dong, Guang Yang, Fangde Liu, Yuanhan Mo, Yike Guo
    Medical Image Understanding and Analysis (MIUA) 2017 (Oral)
    [Paper]
    TensorDB: Database Infrastructure for Continuous Machine Learning
    Fangde Liu, Axel Oehmichen, Jingqing Zhang, Kai Sun, Hao Dong, Yuanman Mo, Yike Guo
    International Conference Artificial Intelligence (ICAI) 2017
    [Paper]
    A New Soft Material based In-the-Ear EEG Recording Technique
    Hao Dong, Paul M Matthews, Yike Guo
    Int. Eng. in Medicine and Biology Conf. (EMBC) 2016 (Oral)
    [Paper]
    DropNeuron: Simplifying the Structure of Deep Neural Networks
    Wei Pan, Hao Dong, Yike Guo
    arXiv:1606.07326 2016
    [Paper] [Code]