publications

2026

1. 

   SIAM: Towards Generalizable Articulated Object Modeling via Single Robot-Object Interactions

   Yuyan Liu, Li Zhang, Di Wu, and 5 more authors

   In the AAAI Conference on Artificial Intelligence, 2026

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2. 

   Exploring Category-level Articulated Object Pose Tracking on SE (3) Manifolds

   Xianhui Meng, Yukang Huo, Li Zhang, and 6 more authors

   In the AAAI Conference on Artificial Intelligence, 2026

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2025

1. 

   PanDiT: A Few-Step Diffusion Transformer for High-Fidelity and Efficient Pansharpening

   Jiabin Fang, Ke Cao, Xuanhua He, and 3 more authors

   IEEE Transactions on Geoscience and Remote Sensing, 2025

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2. 

   Reartgs: Reconstructing and generating articulated objects via 3d gaussian splatting with geometric and motion constraints

   Di Wu, Liu Liu, Zhou Linli, and 5 more authors

   In Conference on Neural Information Processing Systems, 2025

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3. Generalizable and Actionable Part Detection and Manipulation with SAM-Rectified Segmentation and Iterative Pose Refinement

   Sucheng Qian, Li Zhang, Wei Yanyan, and 2 more authors

   In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025
4. ArtGS: 3D Gaussian Splatting for Interactive Visual-Physical Modeling and Manipulation of Articulated Objects

   Qiaojun Yu, Xibin Yuan, Junting Chen, and 8 more authors

   In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2025

5. 

   DFGAP: Towards Depth-Free Cross-Category GAParts Perception via Uncertainty-Quantified Modeling

   Xueyu Yuan, Jiarui Zhang, Jiangqi Song, and 5 more authors

   In ACM International Conference on Multimedia, 2025

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6. 

   Pre-defined keypoints promote category-level articulation pose estimation via multi-modal alignment

   Wenbo Xu, Li Zhang, Liu Liu, and 4 more authors

   In International Joint Conference on Artificial Intelligence, 2025

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7. 

   GaPT-DAR: Category-level Garments Pose Tracking via Integrated 2D Deformation and 3D Reconstruction

   Li Zhang, Mingliang Xu, Jianan Wang, and 6 more authors

   In IEEE Conference on Computer Vision and Pattern Recognition, 2025

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   @inproceedings{zhang2025gapt,
     title = {GaPT-DAR: Category-level Garments Pose Tracking via Integrated 2D Deformation and 3D Reconstruction},
     author = {Zhang, Li and Xu, Mingliang and Wang, Jianan and Yu, Qiaojun and Yang, Lixin and Li, Yonglu and Lu, Cewu and Wang, Rujing and Liu, Liu},
     booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
     pages = {22638--22647},
     year = {2025},
     doi = {10.1109/CVPR52734.2025.02108},
   }

8. 

   R2-Art: Category-Level Articulation Pose Estimation from Single RGB Image via Cascade Render Strategy

   Li Zhang, Haonan Jiang, Yukang Huo, and 5 more authors

   In the AAAI Conference on Artificial Intelligence, 2025

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   @inproceedings{zhang2025r,
     title = {R2-Art: Category-Level Articulation Pose Estimation from Single RGB Image via Cascade Render Strategy},
     author = {Zhang, Li and Jiang, Haonan and Huo, Yukang and Zhong, Yan and Wang, Jianan and Wang, Xue and Wang, Rujing and Liu, Liu},
     booktitle = {the AAAI Conference on Artificial Intelligence},
     volume = {39},
     number = {9},
     pages = {9985--9993},
     year = {2025},
     doi = {10.1609/aaai.v39i9.33083},
   }

9. 

   Rethinking Image Forgery Detection and Localization via Regression Perspective

   Li Zhang, Dong Li, Yan Zhong, and 5 more authors

   IEEE Transactions on Emerging Topics in Computational Intelligence, 2025

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   @article{zhang2025rethinking,
     author = {Zhang, Li and Li, Dong and Zhong, Yan and Zhu, Jiaying and Wang, Rujing and Wu, Xingyu and Wang, Xue and Liu, Liu},
     journal = {IEEE Transactions on Emerging Topics in Computational Intelligence},
     title = {Rethinking Image Forgery Detection and Localization via Regression Perspective},
     year = {2025},
     volume = {},
     number = {},
     pages = {1-13},
     doi = {10.1109/TETCI.2025.3543837},
   }

10. 

    UA-LIO: An Uncertainty-Aware LiDAR-Inertial Odometry for Autonomous Driving in Urban Environments

    Qi Wu, Xieyuanli Chen, Xiangyu Xu, and 7 more authors

    IEEE Transactions on Instrumentation and Measurement, 2025

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    @article{wu2025ualio,
      author = {Wu, Qi and Chen, Xieyuanli and Xu, Xiangyu and Zhong, Xinliang and Qu, Xingwei and Xia, Songpengcheng and Liu, Guoqing and Liu, Liu and Yu, Wenxian and Pei, Ling},
      journal = {IEEE Transactions on Instrumentation and Measurement},
      title = {UA-LIO: An Uncertainty-Aware LiDAR-Inertial Odometry for Autonomous Driving in Urban Environments},
      year = {2025},
      volume = {74},
      number = {},
      pages = {1-12},
      doi = {10.1109/TIM.2025.3544286},
    }

11. 

    Towards Robust Category-level Articulation Pose Estimation via Integrated Differentiable Rendering

    Xinyi Yu, Haonan Jiang, Li Zhang, and 7 more authors

    In IEEE International Conference on Acoustics, Speech and Signal Processing, 2025

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    @inproceedings{yu2025towards,
      title = {Towards Robust Category-level Articulation Pose Estimation via Integrated Differentiable Rendering},
      author = {Yu, Xinyi and Jiang, Haonan and Zhang, Li and Huo, Yukang and Wu, Lin Yuanbo and Wei, Yanyan and Agarwal, Rohit and Shende, Harshal Suresh and Liu, Liu and Ou, Linlin},
      booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
      pages = {1--5},
      year = {2025},
      organization = {IEEE},
      doi = {10.1109/ICASSP49660.2025.10889272},
    }

12. 

    Generalizable Articulated Object Perception with Superpoints

    Qiaojun Yu, Ce Hao, Xibin Yuan, and 5 more authors

    In IEEE International Conference on Acoustics, Speech and Signal Processing, 2025

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    @inproceedings{yu2025generalizable,
      title = {Generalizable Articulated Object Perception with Superpoints},
      author = {Yu, Qiaojun and Hao, Ce and Yuan, Xibin and Zhang, Li and Liu, Liu and Huo, Yukang and Agarwal, Rohit and Lu, Cewu},
      booktitle = {IEEE International Conference on Acoustics, Speech and Signal Processing},
      pages = {1--5},
      year = {2025},
      organization = {IEEE},
      doi = {10.1109/ICASSP49660.2025.10890874},
    }

13. 

    EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation

    Xinyi Yu, Haonan Jiang, Li Zhang, and 3 more authors

    In Conference on Neural Information Processing Systems, 2025

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    @inproceedings{yuefficientcaper,
      title = {EfficientCAPER: An End-to-End Framework for Fast and Robust Category-Level Articulated Object Pose Estimation},
      author = {Yu, Xinyi and Jiang, Haonan and Zhang, Li and Wu, Lin Yuanbo and Ou, Linlin and Liu, Liu},
      booktitle = {Conference on Neural Information Processing Systems},
      year = {2025},
    }

14. 

    Rethinking 3D Convolution in lp $-norm Space

    Li Zhang, Yan Zhong, Jianan Wang, and 3 more authors

    In Conference on Neural Information Processing Systems, 2025

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    @inproceedings{zhangrethinking,
      title = {Rethinking 3D Convolution in lp $-norm Space},
      author = {Zhang, Li and Zhong, Yan and Wang, Jianan and Min, Zhe and Liu, Liu and others},
      booktitle = {Conference on Neural Information Processing Systems},
      year = {2025},
    }

15. 

    U-COPE: Taking a Further Step to Universal 9D Category-Level Object Pose Estimation

    Li Zhang, Weiqing Meng, Yan Zhong, and 6 more authors

    In European Conference on Computer Vision, 2025

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    @inproceedings{zhang2025u,
      title = {U-COPE: Taking a Further Step to Universal 9D Category-Level Object Pose Estimation},
      author = {Zhang, Li and Meng, Weiqing and Zhong, Yan and Kong, Bin and Xu, Mingliang and Du, Jianming and Wang, Xue and Wang, Rujing and Liu, Liu},
      booktitle = {European Conference on Computer Vision},
      pages = {254--270},
      year = {2025},
      organization = {Springer},
      doi = {10.1007/978-3-031-72684-2_15},
    }

2024

1. 

   Gamma: Generalizable articulation modeling and manipulation for articulated objects

   Qiaojun Yu, Junbo Wang, Wenhai Liu, and 5 more authors

   In IEEE International Conference on Robotics and Automation, 2024

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   @inproceedings{yu2024gamma,
     title = {Gamma: Generalizable articulation modeling and manipulation for articulated objects},
     author = {Yu, Qiaojun and Wang, Junbo and Liu, Wenhai and Hao, Ce and Liu, Liu and Shao, Lin and Wang, Weiming and Lu, Cewu},
     booktitle = {IEEE International Conference on Robotics and Automation},
     pages = {5419--5426},
     year = {2024},
     organization = {IEEE},
     doi = {10.1109/ICRA57147.2024.10610652},
   }

2. 

   KPA-Tracker: Towards Robust and Real-Time Category-Level Articulated Object 6D Pose Tracking

   Liu Liu, Anran Huang, Qi Wu, and 3 more authors

   In the AAAI Conference on Artificial Intelligence, 2024

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   @inproceedings{liu2024kpa,
     title = {KPA-Tracker: Towards Robust and Real-Time Category-Level Articulated Object 6D Pose Tracking},
     author = {Liu, Liu and Huang, Anran and Wu, Qi and Guo, Dan and Yang, Xun and Wang, Meng},
     booktitle = {the AAAI Conference on Artificial Intelligence},
     volume = {38},
     number = {4},
     pages = {3684--3692},
     year = {2024},
     doi = {10.1609/aaai.v38i4.28158},
   }

3. 

   RPMArt: Towards Robust Perception and Manipulation for Articulated Objects

   Junbo Wang, Wenhai Liu, Qiaojun Yu, and 4 more authors

   In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

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   @inproceedings{wang2024rpmart,
     author = {Wang, Junbo and Liu, Wenhai and Yu, Qiaojun and You, Yang and Liu, Liu and Wang, Weiming and Lu, Cewu},
     booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
     title = {RPMArt: Towards Robust Perception and Manipulation for Articulated Objects},
     year = {2024},
     pages = {7270-7277},
     doi = {10.1109/IROS58592.2024.10802368},
   }

4. 

   Thermal-NeRF: Neural Radiance Fields from an Infrared Camera

   Tianxiang Ye, Qi Wu, Junyuan Deng, and 6 more authors

   In IEEE/RSJ International Conference on Intelligent Robots and Systems, 2024

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   @inproceedings{ye2024thermal,
     author = {Ye, Tianxiang and Wu, Qi and Deng, Junyuan and Liu, Guoqing and Liu, Liu and Xia, Songpengcheng and Pang, Liang and Yu, Wenxian and Pei, Ling},
     booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
     title = {Thermal-NeRF: Neural Radiance Fields from an Infrared Camera},
     year = {2024},
     pages = {1046-1053},
     doi = {10.1109/IROS58592.2024.10802480},
   }

5. 

   ICAF-4: An Integrated Framework of Category-level Articulated Object Perception and Manipulation for Embodied Intelligence

   WenBo Xu, Li Zhang, Qiankun Li, and 3 more authors

   In British Machine Vision Conference, 2024

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   @inproceedings{Xu_2024_BMVC,
     author = {Xu, WenBo and Zhang, Li and Li, Qiankun and Wu, Qi and Wu, Lin Yuanbo and Liu, Liu},
     title = {ICAF-4: An Integrated Framework of Category-level Articulated Object Perception and Manipulation for Embodied Intelligence},
     booktitle = {British Machine Vision Conference},
     publisher = {BMVA},
     year = {2024},
   }

6. 

   High-throughput spike detection and refined segmentation for wheat Fusarium Head Blight in complex field environments

   Qiong Zhou, Ziliang Huang, Liu Liu, and 5 more authors

   Computers and Electronics in Agriculture, 2024

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2023

1. 

   Category-level articulated object 9d pose estimation via reinforcement learning

   Liu Liu, Jianming Du, Hao Wu, and 4 more authors

   In Proceedings of the 31st ACM International Conference on Multimedia, 2023

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   @inproceedings{liu2023category,
     title = {Category-level articulated object 9d pose estimation via reinforcement learning},
     author = {Liu, Liu and Du, Jianming and Wu, Hao and Yang, Xun and Liu, Zhenguang and Hong, Richang and Wang, Meng},
     booktitle = {Proceedings of the 31st ACM International Conference on Multimedia},
     pages = {728--736},
     year = {2023},
     doi = {10.1145/3581783.3611852},
   }

2. 

   Reaper: Articulated Object 6d Pose Estimation with Deep Reinforcement Learning

   Liu Liu, Qi Wu, Zhendong Xue, and 2 more authors

   In IEEE International Conference on Image Processing, 2023

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   @inproceedings{liu2023reaper,
     title = {Reaper: Articulated Object 6d Pose Estimation with Deep Reinforcement Learning},
     author = {Liu, Liu and Wu, Qi and Xue, Zhendong and Qian, Sucheng and Li, Rui},
     booktitle = {IEEE International Conference on Image Processing},
     pages = {21--25},
     year = {2023},
     organization = {IEEE},
     doi = {10.1109/ICIP49359.2023.10223108},
   }

3. 

   Cellular Network Traffic Prediction Based on Correlation ConvLSTM and Self-Attention Network

   Xuesen Ma, Biao Zheng, Gonghui Jiang, and 1 more author

   IEEE Communications Letters, 2023

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   @article{ma2023cellular,
     title = {Cellular Network Traffic Prediction Based on Correlation ConvLSTM and Self-Attention Network},
     author = {Ma, Xuesen and Zheng, Biao and Jiang, Gonghui and Liu, Liu},
     journal = {IEEE Communications Letters},
     volume = {27},
     number = {7},
     pages = {1909--1912},
     year = {2023},
     publisher = {IEEE},
     doi = {10.1109/LCOMM.2023.3275327},
   }

2022

1. 

   Akb-48: A real-world articulated object knowledge base

   Liu Liu, Wenqiang Xu, Haoyuan Fu, and 4 more authors

   In IEEE Conference on Computer Vision and Pattern Recognition, 2022

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   @inproceedings{liu2022akb,
     title = {Akb-48: A real-world articulated object knowledge base},
     author = {Liu, Liu and Xu, Wenqiang and Fu, Haoyuan and Qian, Sucheng and Yu, Qiaojun and Han, Yang and Lu, Cewu},
     booktitle = {IEEE Conference on Computer Vision and Pattern Recognition},
     pages = {14809--14818},
     year = {2022},
     doi = {10.1109/CVPR52688.2022.01439},
   }

2. 

   Oakink: A large-scale knowledge repository for understanding hand-object interaction

   Lixin Yang, Kailin Li, Xinyu Zhan, and 4 more authors

   In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, 2022

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   @inproceedings{yang2022oakink,
     title = {Oakink: A large-scale knowledge repository for understanding hand-object interaction},
     author = {Yang, Lixin and Li, Kailin and Zhan, Xinyu and Wu, Fei and Xu, Anran and Liu, Liu and Lu, Cewu},
     booktitle = {Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
     pages = {20953--20962},
     year = {2022},
     doi = {10.1109/CVPR52688.2022.02028},
   }

3. 

   Toward real-world category-level articulation pose estimation

   Liu Liu, Han Xue, Wenqiang Xu, and 2 more authors

   IEEE Transactions on Image Processing, 2022

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   @article{liu2022toward,
     title = {Toward real-world category-level articulation pose estimation},
     author = {Liu, Liu and Xue, Han and Xu, Wenqiang and Fu, Haoyuan and Lu, Cewu},
     journal = {IEEE Transactions on Image Processing},
     volume = {31},
     pages = {1072--1083},
     publisher = {IEEE},
     year = {2022},
     doi = {10.1109/TIP.2021.3138644},
   }

4. 

   When pansharpening meets graph convolution network and knowledge distillation

   Keyu Yan, Man Zhou, Liu Liu, and 2 more authors

   IEEE Transactions on Geoscience and Remote Sensing, 2022

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   @article{yan2022pansharpening,
     title = {When pansharpening meets graph convolution network and knowledge distillation},
     author = {Yan, Keyu and Zhou, Man and Liu, Liu and Xie, Chengjun and Hong, Danfeng},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     volume = {60},
     pages = {1--15},
     year = {2022},
     publisher = {IEEE},
     doi = {10.1109/TGRS.2022.3168192},
   }

5. 

   Towards densely clustered tiny pest detection in the wild environment

   Jianming Du, Liu Liu, Rui Li, and 3 more authors

   Neurocomputing, 2022

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   @article{du2022towards,
     title = {Towards densely clustered tiny pest detection in the wild environment},
     author = {Du, Jianming and Liu, Liu and Li, Rui and Jiao, Lin and Xie, Chengjun and Wang, Rujing},
     journal = {Neurocomputing},
     volume = {490},
     pages = {400--412},
     year = {2022},
     publisher = {Elsevier},
     doi = {10.1016/j.neucom.2021.12.012},
   }

6. 

   A global activated feature pyramid network for tiny pest detection in the wild

   Liu Liu, Rujing Wang, Chengjun Xie, and 3 more authors

   Machine Vision and Applications, 2022

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   @article{liu2022global,
     title = {A global activated feature pyramid network for tiny pest detection in the wild},
     author = {Liu, Liu and Wang, Rujing and Xie, Chengjun and Li, Rui and Wang, Fangyuan and Qi, Long},
     journal = {Machine Vision and Applications},
     volume = {33},
     number = {5},
     pages = {76},
     year = {2022},
     publisher = {Springer},
     doi = {10.1007/s00138-022-01310-0},
   }

7. 

   A multi-branch convolutional neural network with density map for aphid counting

   Rui Li, Rujing Wang, Chengjun Xie, and 8 more authors

   Biosystems Engineering, 2022

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   @article{li2022multi,
     title = {A multi-branch convolutional neural network with density map for aphid counting},
     author = {Li, Rui and Wang, Rujing and Xie, Chengjun and Chen, Hongbo and Long, Qi and Liu, Liu and Zhang, Jie and Chen, Tianjiao and Hu, Haiying and Jiao, Lin and others},
     journal = {Biosystems Engineering},
     volume = {213},
     pages = {148--161},
     year = {2022},
     publisher = {Elsevier},
     doi = {10.1016/j.biosystemseng.2021.11.020},
   }

8. 

   Fast location and segmentation of high-throughput damaged soybean seeds with invertible neural networks

   Ziliang Huang, Rujing Wang, Qiong Zhou, and 4 more authors

   Journal of the Science of Food and Agriculture, 2022

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   @article{huang2022fast,
     title = {Fast location and segmentation of high-throughput damaged soybean seeds with invertible neural networks},
     author = {Huang, Ziliang and Wang, Rujing and Zhou, Qiong and Teng, Yue and Zheng, Shijian and Liu, Liu and Wang, Liusan},
     journal = {Journal of the Science of Food and Agriculture},
     volume = {102},
     number = {11},
     pages = {4854--4865},
     year = {2022},
     publisher = {Wiley Online Library},
     doi = {10.1002/jsfa.11848},
   }

9. 

   MSR-RCNN: a multi-class crop pest detection network based on a multi-scale super-resolution feature enhancement module

   Yue Teng, Jie Zhang, Shifeng Dong, and 2 more authors

   Frontiers in Plant Science, 2022

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   @article{teng2022msr,
     title = {MSR-RCNN: a multi-class crop pest detection network based on a multi-scale super-resolution feature enhancement module},
     author = {Teng, Yue and Zhang, Jie and Dong, Shifeng and Zheng, Shijian and Liu, Liu},
     journal = {Frontiers in Plant Science},
     volume = {13},
     pages = {810546},
     year = {2022},
     publisher = {Frontiers Media SA},
     doi = {10.3389/fpls.2022.810546},
   }

2021

1. 

   OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval

   Han Xue, Liu Liu, Wenqiang Xu, and 2 more authors

   2021

   Bib HTML PDF

   

   @article{xue2021omad,
     title = {OMAD: Object Model with Articulated Deformations for Pose Estimation and Retrieval},
     author = {Xue, Han and Liu, Liu and Xu, Wenqiang and Fu, Haoyuan and Lu, Cewu},
     year = {2021},
     booktitle = {British Machine Vision Conference},
   }

2. 

   Learning region-guided scale-aware feature selection for object detection

   Liu Liu, Rujing Wang, Chengjun Xie, and 4 more authors

   Neural Computing and Applications, 2021

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   @article{liu2021learning,
     title = {Learning region-guided scale-aware feature selection for object detection},
     author = {Liu, Liu and Wang, Rujing and Xie, Chengjun and Li, Rui and Wang, Fangyuan and Zhou, Man and Teng, Yue},
     journal = {Neural Computing and Applications},
     volume = {33},
     pages = {6389--6403},
     year = {2021},
     publisher = {Springer},
     doi = {10.1109/TII.2020.2995208},
   }

3. 

   ReinforceNet: A reinforcement learning embedded object detection framework with region selection network

   Man Zhou, Rujing Wang, Chengjun Xie, and 4 more authors

   Neurocomputing, 2021

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   @article{zhou2021reinforcenet,
     title = {ReinforceNet: A reinforcement learning embedded object detection framework with region selection network},
     author = {Zhou, Man and Wang, Rujing and Xie, Chengjun and Liu, Liu and Li, Rui and Wang, Fangyuan and Li, Dengshan},
     journal = {Neurocomputing},
     volume = {443},
     pages = {369--379},
     year = {2021},
     publisher = {Elsevier},
     doi = {10.1016/j.neucom.2021.02.073},
   }

4. 

   Reinforcedet: Object Detection By Integrating Reinforcement Learning With Decoupled Pipeline

   Man Zhou, Liu Liu, and Rujing Wang

   In IEEE International Conference on Image Processing, 2021

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   @inproceedings{zhou2021reinforcedet,
     title = {Reinforcedet: Object Detection By Integrating Reinforcement Learning With Decoupled Pipeline},
     author = {Zhou, Man and Liu, Liu and Wang, Rujing},
     booktitle = {IEEE International Conference on Image Processing},
     pages = {2778--2782},
     year = {2021},
     organization = {IEEE},
     doi = {10.1109/ICIP42928.2021.9506038},
   }

5. 

   Convolutional neural network based automatic pest monitoring system using hand-held mobile image analysis towards non-site-specific wild environment

   Fangyuan Wang, Rujing Wang, Chengjun Xie, and 3 more authors

   Computers and Electronics in Agriculture, 2021

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   @article{wang2021convolutional,
     title = {Convolutional neural network based automatic pest monitoring system using hand-held mobile image analysis towards non-site-specific wild environment},
     author = {Wang, Fangyuan and Wang, Rujing and Xie, Chengjun and Zhang, Jie and Li, Rui and Liu, Liu},
     journal = {Computers and Electronics in Agriculture},
     volume = {187},
     pages = {106268},
     year = {2021},
     publisher = {Elsevier},
     doi = {10.1016/j.compag.2021.106268},
   }

2020

1. 

   Deep learning based automatic multiclass wild pest monitoring approach using hybrid global and local activated features

   Liu Liu, Chengjun Xie, Rujing Wang, and 5 more authors

   IEEE Transactions on Industrial Informatics, 2020

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   @article{liu2020deep,
     title = {Deep learning based automatic multiclass wild pest monitoring approach using hybrid global and local activated features},
     author = {Liu, Liu and Xie, Chengjun and Wang, Rujing and Yang, Po and Sudirman, Sud and Zhang, Jie and Li, Rui and Wang, Fangyuan},
     journal = {IEEE Transactions on Industrial Informatics},
     volume = {17},
     number = {11},
     pages = {7589--7598},
     year = {2020},
     publisher = {IEEE},
     doi = {10.1007/s00521-020-05400-w},
   }

2. 

   Fpha-afford: A domain-specific benchmark dataset for occluded object affordance estimation in human-object-robot interaction

   Liu Liu, Wenqiang Xu, Cewu Lu, and 1 more author

   In IEEE International Conference on Image Processing, 2020

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   @inproceedings{liu2020fpha,
     title = {Fpha-afford: A domain-specific benchmark dataset for occluded object affordance estimation in human-object-robot interaction},
     author = {Liu, Liu and Xu, Wenqiang and Lu, Cewu and others},
     booktitle = {IEEE International Conference on Image Processing},
     pages = {1416--1420},
     year = {2020},
     organization = {IEEE},
     doi = {10.1109/ICIP40778.2020.9190733},
   }

3. 

   An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild

   Yushan Zhao, Liu Liu, Chengjun Xie, and 4 more authors

   Applied Soft Computing, 2020

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   @article{zhao2020effective,
     title = {An effective automatic system deployed in agricultural Internet of Things using Multi-Context Fusion Network towards crop disease recognition in the wild},
     author = {Zhao, Yushan and Liu, Liu and Xie, Chengjun and Wang, Rujing and Wang, Fangyuan and Bu, Yingqiao and Zhang, Shunxiang},
     journal = {Applied Soft Computing},
     volume = {89},
     pages = {106128},
     year = {2020},
     publisher = {Elsevier},
     doi = {10.1016/j.asoc.2020.106128},
   }

4. 

   Fusing multi-scale context-aware information representation for automatic in-field pest detection and recognition

   Fangyuan Wang, Rujing Wang, Chengjun Xie, and 2 more authors

   Computers and Electronics in Agriculture, 2020

   DOI Bib HTML PDF

   

   @article{wang2020fusing,
     title = {Fusing multi-scale context-aware information representation for automatic in-field pest detection and recognition},
     author = {Wang, Fangyuan and Wang, Rujing and Xie, Chengjun and Yang, Po and Liu, Liu},
     journal = {Computers and Electronics in Agriculture},
     volume = {169},
     pages = {105222},
     year = {2020},
     publisher = {Elsevier},
     doi = {10.1016/j.compag.2020.105222},
   }

2019

1. 

   Deep learning based automatic approach using hybrid global and local activated features towards large-scale multi-class pest monitoring

   Liu Liu, Rujing Wang, Chengjun Xie, and 4 more authors

   In 2019 IEEE 17th International Conference on Industrial Informatics (INDIN), 2019

   DOI Bib HTML PDF

   

   @inproceedings{liu2019deep,
     title = {Deep learning based automatic approach using hybrid global and local activated features towards large-scale multi-class pest monitoring},
     author = {Liu, Liu and Wang, Rujing and Xie, Chengjun and Yang, Po and Sudirman, S and Wang, F and Li, R},
     booktitle = {2019 IEEE 17th International Conference on Industrial Informatics (INDIN)},
     volume = {1},
     pages = {1507--1510},
     year = {2019},
     doi = {10.1109/INDIN41052.2019.8972026},
   }

2. 

   A coarse-to-fine network for aphid recognition and detection in the field

   Rui Li, Rujing Wang, Chengjun Xie, and 4 more authors

   Biosystems engineering, 2019

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   @article{li2019coarse,
     title = {A coarse-to-fine network for aphid recognition and detection in the field},
     author = {Li, Rui and Wang, Rujing and Xie, Chengjun and Liu, Liu and Zhang, Jie and Wang, Fangyuan and Liu, Wancai},
     journal = {Biosystems engineering},
     volume = {187},
     pages = {39--52},
     year = {2019},
     publisher = {Elsevier},
     doi = {10.1016/j.biosystemseng.2019.08.013},
   }