@inproceedings {pointwisecnn_cvpr2018,

conference = {2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},

title = {Pointwise Convolutional Neural Networks},

author = {Binh-Son Hua, Minh-Khoi Tran, Sai-Kit Yeung},

year = {2018}

}

@inproceedings {uncalib_photo_NI,

conference = {2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},

title = {Uncalibrated Photometric Stereo under Natural Illumination},

author = {Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita},

year = {2018}

}

@inproceedings {sefl_calib_polradiometric,

conference = {2018 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},

title = {Self-calibrating polarising radiometric calibration},

author = {Daniel Teo Guangwei, Boxin Shi, Yinqiang Zheng, Sai-Kit Yeung},

year = {2018}

}

@inproceedings {unsupervisedSkeletonExtract,

conference = {The Thirty-Second AAAI Conference on Artificial Intelligence},

title = {Unsupervised Articulated Skeleton Extraction from Point Set Sequences Captured by a Single Depth Camera},

author = {Xuequan Lu, Honghua Chen, Sai-Kit Yeung, Zhigang Deng, Wenzhi Chen},

year = {2018}

}

@article{ma2018language,
title={Language-Driven Synthesis of 3D Scenes from Scene Databases}, 
author={Ma, Rui and Gadi Patil, Akshay and Fisher, Matthew and Li, Manyi and Pirk, Sören and Hua, Binh-Son and Yeung, Sai-Kit and Tong, Xin and Guibas, Leonidas and Zhang, Hao}, 
journal={ACM Transactions on Graphics (TOG)}, 
volume={37}, 
number={6}, 
year={2018},
publisher={ACM}
}

@inproceedings{eccv18_zoning,
author = "Tian Feng and Quang-Trung Truong and Thanh Nguyen and Jing Yu Koh and Lap-Fai Yu and Alexander Binder and Sai-Kit Yeung",
title = "Urban Zoning Using Higher-Order Markov Random Fields on Multi-View Imagery Data",
booktitle = "European Conference on Computer Vision (ECCV)",
year = "2018"
}

@inproceedings{ismar18_dualgaze,
author = "Pallavi Mohan, Wooi Boon Goh, Chi-Wing Fu, and Sai-Kit Yeung",
title = "DualGaze: addressing the midas touch problem in gaze mediated VR interaction",
booktitle = "In Adjunct Proceedings of the IEEE and ACM International Symposium for Mixed and Augmented Reality (ISMAR), 2018",
year = "2018"
} 

@inproceedings{wacv19_hieu,
author = "Quang-Hieu Pham, Binh-Son Hua, Duc Thanh Nguyen, Sai-Kit Yeung",
title = "Real-time Progressive 3D Semantic Segmentation for Indoor Scenes",
booktitle = "IEEE Winter Conf. on Applications of Computer Vision (WACV 2019) ",
year = "2019"
} 

@inproceedings {3dor.20181052,
booktitle = {Eurographics Workshop on 3D Object Retrieval},
editor = {Telea, Alex and Theoharis, Theoharis and Veltkamp, Remco},
title = {{RGB-D Object-to-CAD Retrieval}},
author = {Pham, Quang-Hieu and Tran, Minh-Khoi and Li, Wenhui and Xiang, Shu and Zhou, Heyu and Nie, Weizhi and Liu, Anan and Su, Yuting and Tran, Minh-Triet and Bui, Ngoc-Minh and Do, Trong-Le and Ninh, Tu V. and Le, Tu-Khiem and Dao, Anh-Vu and Nguyen, Vinh-Tiep and Do, Minh N. and Duong, Anh-Duc and Hua, Binh-Son and Yu, Lap-Fai and Nguyen, Duc Thanh and Yeung, Sai-Kit},
year = {2018},
publisher = {The Eurographics Association},
ISSN = {1997-0471},
ISBN = {978-3-03868-053-6},
DOI = {10.2312/3dor.20181052}
}

@Article{Weeger2018textilesACMA,
  author =    {Weeger, O. and Sakhaei, A.H. and Tan, Y.Y. and Quek, Y.H. and Lee, T. L. and Yeung, S.-K. and Kaijima, S. and Dunn, M.L.},
  title =     {Nonlinear multi-scale modelling, simulation and validation of 3D knitted textiles},
  journal =   {Applied Composite Materials},
  volume =    {25},
  number =     {4},
  pages =     {797--810},
  year =      {2018},
  doi =       {10.1007/s10443-018-9702-4},
  abstract =  {Three-dimensionally (3D) knitted technical textiles are spreading into industrial applications, since their geometric, structural and functional performance can be tailored and optimized on fibre-, yarn- and fabric levels by customizing yarn materials, knit patterns and geometric shapes. The ability to simulate their complex mechanical behaviour is thus an essential ingredient in the development of a digital workflow for optimal design and manufacture of 3D knitted textiles. Here, we present a multi-scale modelling and simulation framework for the prediction of the nonlinear orthotropic mechanical behaviour of single jersey knitted textiles and its experimental validation. On the meso-scale, representative volume elements (RVEs) of the fabric are modelled as single, interlocked yarn loops and their mechanical deformation behaviour is homogenized using periodic boundary conditions. Yarns are modelled as nonlinear 3D beam elements and numerically discretized using an isogeometric collocation method, where a frictional contact formulation is used to model inter-yarn interactions. On the macro-scale, fabrics are modelled as membrane elements with nonlinear orthotropic material behaviour, which is parameterized by a response surface constitutive model obtained from the meso-scale homogenization. The input parameters of the yarn-level simulation, i.e., mechanical properties of yarns and geometric dimensions of yarn loops in the fabrics, are determined experimentally and subsequent meso- and macro-scale simulation results are evaluated against reference results and mechanical tests of knitted fabric samples. Good agreement between computational predictions and experimental results is achieved for samples with varying stitch values, thus validating our novel computational approach combining efficient meso-scale simulation using 3D beam modelling of yarns with numerical homogenization and nonlinear orthotropic response surface constitutive modelling on the macro-scale.}
}

@article{traffic19,
author = {Qianwen Chao and Xiaogang Jin and Hen-Wei Huang and Shaohui Foong and Lap-Fai Yu and Sai-Kit Yeung},
    title = {Force-based Heterogeneous Traffic Simulation for Autonomous Vehicle Testing},
    journal = {IEEE International Conference on Robotics and Automation},
    year = {2019}
}

@inproceedings{pham2020lcd,
  title = {{LCD}: {L}earned cross-domain descriptors for 2{D}-3{D} matching},
  author = {Pham, Quang-Hieu and Uy, Mikaela Angelina and Hua, Binh-Son and Nguyen, Duc Thanh and Roig, Gemma and Yeung, Sai-Kit},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year = 2020
}

@inproceedings{huang2020dualslam,
      title={Dual-SLAM: A framework for robust single camera navigation}, 
      author={Huajian Huang and Wen-Yan Lin and Siying Liu and Dong Zhang and Sai-Kit Yeung},
	  booktitle = {IEEE/RSJ International Conference on Intelligent Robots and Systems},
	  year = 2020
}

@inproceedings{inproceedings,
author = {Zhang, Zhiyuan and Hua, Binh-Son and Chen, Wei and Tian, Yibin and Yeung, Sai-Kit},
year = {2020},
month = {11},
pages = {210-219},
title = {Global Context Aware Convolutions for 3D Point Cloud Understanding},
doi = {10.1109/3DV50981.2020.00031}
}

@inproceedings{koh2020sideinfnet,
author = {Koh, Jing Yu and Nguyen, Duc Thanh and Truong, Quang-Trung and Yeung, Sai-Kit and Binder, Alexander},
year = {2020},
title = {SideInfNet: A Deep Neural Network for Semi-Automatic Semantic Segmentation with Side Information},
booktitle = {European Conference on Computer Vision},
}

@article{Bian2020gms,
  title={{GMS}: Grid-based Motion Statistics for Fast, Ultra-Robust Feature Correspondence},
  author={Bian,Jia-Wang and Lin,Wen-Yan and Liu,Yun and Zhang,Le and Yeung,Sai-Kit and Cheng,Ming-Ming and Reid,Ian},
  journal={International Journal of Computer Vision (IJCV)},
  year={2020}
}

@article{xuequan2019_skeleton,
  title={3D Articulated Skeleton Extraction Using a Single Consumer-Grade Depth Camera},
  author={Xuequan Lu, Zhigang Deng, Jun Luo, Wenzhi Chen, Sai-Kit Yeung, Ying He},
  journal={Computer Vision and Image Understanding (CVIU)},
  year={2019}
}

@article{zhipeng2019_TPAMI,
  title={Ambiguity-Free Radiometric Calibration for Internet Photo Collections},
  author={Zhipeng Mo, Boxin Shi, Sai-Kit Yeung, Yasuyuki Matsushita},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)},
  year={2019}
}

@inproceedings{uy-scanobjectnn-iccv19,
      title = {Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data},
      author = {Mikaela Angelina Uy and Quang-Hieu Pham and Binh-Son Hua and Duc Thanh Nguyen and Sai-Kit Yeung},
      booktitle = {International Conference on Computer Vision (ICCV)},
      year = {2019}
  }

@inproceedings{zhang-shellnet-iccv19,
    title = {ShellNet: Efficient Point Cloud Convolutional Neural Networks using Concentric Shells Statistics},
    author = {Zhiyuan Zhang and Binh-Son Hua and Sai-Kit Yeung},
    booktitle = {International Conference on Computer Vision (ICCV)},
    year = {2019}
}

@inproceedings{zhang-riconv-3dv19,
    title = {Rotation Invariant Convolutions for 3D Point Clouds Deep Learning},
    author = {Zhiyuan Zhang and Binh-Son Hua and David W. Rosen and Sai-Kit Yeung},
    booktitle = {International Conference on 3D Vision (3DV)},
    year = {2019}
}

@inproceedings{pham2019jsis3d,
  title = {{JSIS3D}: {J}oint semantic-instance segmentation of 3{D} point clouds with multi-task pointwise networks and multi-value conditional random fields},
  author = {Pham, Quang-Hieu and Nguyen, Duc Thanh and Hua, Binh-Son and Roig, Gemma and Yeung, Sai-Kit},
  booktitle = {IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = 2019
}

@article{knitkit2021,
  author    = {Nader, Georges and Quek, Yu Han and Chia, Pei Zhi and Weeger, Oliver and Yeung, Sai-Kit},
  title     = {KnitKit: A flexible system for machine knitting of customizable textiles},
  journal   = {ACM Transactions on Graphics (TOG)},
  number    = {4},
  volume    = {40},
  year      = {2021},
  publisher = {ACM}
}

@InProceedings{Kim_2021_ICCV,
    author    = {Kim, Jaeyeon and Hua, Binh-Son and Nguyen, Thanh and Yeung, Sai-Kit},
    title     = {Minimal Adversarial Examples for Deep Learning on 3D Point Clouds},
    booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
    month     = {October},
    year      = {2021},
    pages     = {7797-7806}
}

@ARTICLE{9547740,
  author={Guo, Heng and Mo, Zhipeng and Shi, Boxin and Lu, Feng and Yeung, Sai Kit and Tan, Ping and Matsushita, Yasuyuki},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence}, 
  title={Patch-based Uncalibrated Photometric Stereo under Natural Illumination}, 
  year={2021},
  volume={},
  number={},
  pages={1-1},
  doi={10.1109/TPAMI.2021.3115229}}

@INPROCEEDINGS{9812203,  
author={Huang, Huajian and Yeung, Sai-Kit},  
booktitle={2022 International Conference on Robotics and Automation (ICRA)},   
title={360VO: Visual Odometry Using A Single 360 Camera},   
year={2022},  volume={},  number={},  pages={5594-5600},  
doi={10.1109/ICRA46639.2022.9812203}}

	@inproceedings{inproceedings,
author = {Huajian Huang and Sai-Kit Yeung},
year = {2022},
month = {01},
pages = {},
title = {SiamX: An Efficient Long-term Tracker Using Cross-level Feature Correlation and Adaptive Tracking Scheme}
}

	@inproceedings{inproceedings,
author = {Ziqiang Zheng, Huajian Huang, Apple, Pui-Yi Chui, Yue Him Wong, Sai-Kit Yeung},
year = {2022},
title = {Advanced Computer Vision Techniques for Efficient Seafloor Surveying}
}

	@inproceedings{inproceedings,
author = {Zhiyuan Zhang, Binh-Son Hua, Sai-Kit Yeung},
year = {2022},
title = {RIConv++: Effective Rotation Invariant Convolutions for 3D Point Clouds Deep Learning}
}

@article{WEEGER201939,
title = {Digital design and nonlinear simulation for additive manufacturing of soft lattice structures},
journal = {Additive Manufacturing},
volume = {25},
pages = {39-49},
year = {2019},
issn = {2214-8604},
doi = {https://doi.org/10.1016/j.addma.2018.11.003},
url = {https://www.sciencedirect.com/science/article/pii/S2214860417303962},
author = {O. Weeger and N. Boddeti and S.-K. Yeung and S. Kaijima and M.L. Dunn},
keywords = {Lattices, Digital design, Multi-material 3D printing, Soft structures, Functionally graded structures, Nonlinear rods},
abstract = {Lattice structures are frequently found in nature and engineering due to their myriad attractive properties, with applications ranging from molecular to architectural scales. Lattices have also become a key concept in additive manufacturing, which enables precise fabrication of complex lattices that would not be possible otherwise. While design and simulation tools for stiff lattices are common, here we present a digital design and nonlinear simulation approach for additive manufacturing of soft lattices structures subject to large deformations and instabilities, for which applications in soft robotics, healthcare, personal protection, energy absorption, fashion and design are rapidly emerging. Our framework enables design of soft lattices with curved members conforming to freeform geometries, and with variable, gradually changing member thickness and material, allowing the local control of stiffness. We model the lattice members as 3D curved rods and using a spline-based isogeometric method that allows the efficient simulation of nonlinear, large deformation behavior of these structures directly from the CAD geometries. Furthermore, we enhance the formulation with a new joint stiffening approach, which is based on parameters derived from the actual node geometries. Simulation results are verified against experiments with soft lattices realized by PolyJet multi-material polymer 3D printing, highlighting the potential for simulation-driven, digital design and application of non-uniform and curved soft lattice structures.}
}

@article{WEEGER201895,
title = {Fully isogeometric modeling and analysis of nonlinear 3D beams with spatially varying geometric and material parameters},
journal = {Computer Methods in Applied Mechanics and Engineering},
volume = {342},
pages = {95-115},
year = {2018},
issn = {0045-7825},
doi = {https://doi.org/10.1016/j.cma.2018.07.033},
url = {https://www.sciencedirect.com/science/article/pii/S0045782518303669},
author = {Oliver Weeger and Sai-Kit Yeung and Martin L. Dunn},
keywords = {Isogeometric analysis, 3D beams, Spatially varying materials, Functionally graded beams, Collocation method},
abstract = {We present a fully isogeometric modeling and simulation method for geometrically exact, nonlinear 3D beams with spatially varying geometric and material distributions, both along the beam axis and through its cross-section. The approach is based on the modeling of 3D beams using the Cosserat rod theory and the numerical discretization using B-Spline and NURBS parameterizations in an isogeometric collocation method. Transversally varying material constitutions are represented using non-homogeneous, functionally graded beam cross-section definitions such as laminates and continuously graded cross-sections. Furthermore, to model the axial variation of material and geometry, we introduce the parameterization of cross-section properties as spline curves along the beam centerlines. This fully isogeometric modeling and analysis concept, which is based on spline parameterizations of initial beam centerline curves, kinematic unknowns and axially varying material and geometric parameters, has various practical applications enabled by advances in manufacturing technology, including multi-material 3D printing and advanced manufacturing of composites with automated fiber placement. We verify and demonstrate the modeling and simulation approach using several numerical studies and highlight its practical applicability.}
}

@article{DINH201881,
title = {Prediction of mechanical properties of knitted fabrics under tensile and shear loading: Mesoscale analysis using representative unit cells and its validation},
journal = {Composites Part B: Engineering},
volume = {148},
pages = {81-92},
year = {2018},
issn = {1359-8368},
doi = {https://doi.org/10.1016/j.compositesb.2018.04.052},
url = {https://www.sciencedirect.com/science/article/pii/S1359836818302439},
author = {T.D. Dinh and O. Weeger and S. Kaijima and S.-K. Yeung},
keywords = {Knitted fabrics, Multiscale analysis, Numerical homogenization method, Periodic boundary conditions},
abstract = {This article presents a numerical framework to predict the mechanical behavior of knitted fabrics from their discrete structure at the fabric yarn level, i.e., the mesostructure, utilizing the hierarchical multiscale method. Due to the regular distribution of yarn loops in a knitted structure, the homogenization theory for periodic materials can be employed. Thus, instead of considering the whole fabric sample under loading, a significantly less computationally demanding analysis can be done on a repeated unit cell (RUC). This RUC is created based on simple structural parameters of knitted yarn loops and its fabric yarns are assumed to behave transversely isotropic. Nonlinear finite element analyses are performed to determine the stress fields in the RUC under tensile and shear loading. During this analysis, contact friction among yarns is considered as well as the periodic boundary conditions are employed. The macroscopic stresses then can be derived from the stress fields in the RUC by means of the numerical homogenization scheme. The physical fidelity of the proposed framework is shown by the good agreement between the predicted mechanical properties of knitted fabrics and corresponding experimental data.}
}

@article{Chen2016,
author={Chen, Xiang and Xu, Wei-Wei and Yeung, Sai-Kit and Zhou, Kun},
title={View-Aware Image Object Compositing and Synthesis from Multiple Sources},
journal={Journal of Computer Science and Technology},
year={2016},
month={May},
day={01},
volume={31},
number={3},
pages={463-478},
issn={1860-4749},
doi={10.1007/s11390-016-1640-8},
url={https://doi.org/10.1007/s11390-016-1640-8}
}

@INPROCEEDINGS{rfnet4d,
author = {Vu, Tuan and Nguyen, Duc-Thanh and Hua, Binh-Son and Pham, Quang-Hieu and Yeung, Sai-Kit},
year = {2022},
title = {RFNet-4D: Joint Object Reconstruction and Flow Estimation from 4D Point Clouds},
 booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)}
}

@article{DBLP:journals/corr/abs-2108-01806,
  author    = {Hong{-}Wing Pang and
               Yingshu Chen and
               Binh{-}Son Hua and
               Sai{-}Kit Yeung},
  title     = {Neural Scene Decoration from a Single Photograph},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2022}
}

@INPROCEEDINGS{360STMapping_Huajian,  
author={Hongji Liu, Huajian Huang, Sai-Kit Yeung, Ming Liu},  
booktitle={2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},   
title={360ST-Mapping: An Online Semantics-Guided topological mapping Module for Omnidirectional Visual SLAM},   
year={2022}}

@proceedings{susan_timeofday,
  author    = {Yingshu Chen, Tuan-Anh Vu, Ka-Chun Shum, Binh-Son Hua, Sai-Kit Yeung},
  title     = {Time-of-Day Neural Style Transfer for Architectural Photographs},
  booktitle = {{IEEE} International Conference on Computational Photography, {ICCP}
               2022},
  publisher = {{IEEE}},
  year      = {2022},
}

@inproceedings{MVK,
    title     = {Marine Video Kit: A New Marine Video Dataset for Content-based Analysis and Retrieval},
    author    = {Truong, Quang-Trung and Vu, Tuan-Anh and Ha, Tan-Sang and Lokoč, Jakub and Tim,
                Yue Him Wong and Joneja, Ajay and Yeung, Sai-Kit},
    publisher = {Springer},
    year      = {2023},
    booktitle = {MultiMedia Modeling - 29th International Conference, {MMM} 2023,
                Bergen, Norway, January 9-12, 2023}
}

@article{jy-pointinverter-wacv23,
      title = {PointInverter: Point Cloud Reconstruction and Editing via a Generative Model with Shape Priors},
      author = {Jaeyeon Kim and Binh-Son Hua and Duc Thanh Nguyen and Sai-Kit Yeung},
      booktitle = {IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)},
      year = {2023}
  }

@article{fisheryPlatform,
      title = {A Novel Platform to Control Biofouling in Pearl Oysters Cultivation},
      author = {Van-Nhan Tran, Quan-Dung Pham, Tan-Sang Ha, Yue Him Wong, Sai-Kit Yeung},
      booktitle = {IEEE International Conference on Robotics and Automation (ICRA)},
      year = {2023}
  }

@article{ocean23_mvc,
      title = {Marine Video Cloud: A Cloud-Based Video Analytics Platform for Collaborative Marine Research},
      author = {Ziqiang Zheng, Tan-Sang Ha, Yingshu Chen, Haixin Liang, Apple Pui-Yi Chui, Yue-Him Wong, Sai-Kit Yeung},
      booktitle = {OCEANS 2023, Limerick},
      year = {2023}
}

@article{ocean23_marinevrs,
      title = {MarineVRS: Marine Video Retrieval System with Explainability via Semantic Understanding},
      author = {Tan-Sang Ha, Hai Nguyen-Truong, Tuan-Anh Vu, Sai-Kit Yeung},
      booktitle = {OCEANS 2023, Limerick},
      year = {2023}
  }

    @InProceedings{huang360VOT,
      author = {Huajian Huang, Yinzhe Xu, Yingshu Chen and Sai-Kit Yeung},
      title = {360VOT: A New Benchmark Dataset for Omnidirectional Visual Object Tracking},
      booktitle = {Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)},
      month = {October},
      year = {2023},
      pages = {}
      }
  

      @article{shum2023conditional,
        title={Conditional 360-degree Image Synthesis for Immersive Indoor Scene Decoration},
        author={Shum, Ka Chun and Pang, Hong-Wing and Hua, Binh-Son and Nguyen, Duc Thanh and Yeung, Sai-Kit},
        journal={arXiv preprint arXiv:2307.09621},
        year={2023}
      }
    

		@inproceedings{pang-nerfstyle-iccv23,
		title = {Locally Stylized Neural Radiance Fields},
		author = {Hong-Wing Pang and Binh-Son Hua and Sai-Kit Yeung},
		booktitle = {International Conference on Computer Vision (ICCV)},
		year = {2023}
		}
    

        @inproceedings{zheng2023cap,
          title={Cross-Domain Autonomous Driving Perception using Contrastive Appearance Adaptation},
          author={Ziqiang Zheng and Yingshu Chen and Binh-Son Hua and Yang Wu and Sai-Kit Yeung},
          booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
          year={2023}
          organization={IEEE}
        }
      

      @inproceedings{zheng2023compuda,
        title={CompUDA: Compositional Unsupervised Domain Adaptation for Semantic Segmentation under Adverse Conditions},
        author={Ziqiang Zheng and Yingshu Chen and Binh-Son Hua and Sai-Kit Yeung},
        booktitle={2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
        year={2023}
        organization={IEEE}
      }
    

    @article{ziqiang_gan-slam23,
      title={Real-time GAN-based image enhancement for robust underwater monocular SLAM},
      author={Zheng, Ziqiang and Xin, Zhichao and Yu, Zhibin and Yeung, Sai-Kit},
      journal={Frontiers in Marine Science},
      year={2023},
      publisher={Frontiers Research Foundation}
    }
  

    @article{pham2023uwa360cam,
      title={UWA360CAM: A 360$\^{}$\{$$\backslash$circ$\}$ $24/7 Real-Time Streaming Camera System for Underwater Applications},
      author={Pham, Quan-Dung and Zhu, Yipeng and Ha, Tan-Sang and Nguyen, KH and Hua, Binh-Son and Yeung, Sai-Kit},
      journal={arXiv preprint arXiv:2309.12668},
      year={2023}
    }
  

    @inproceedings{tavu2024tta,
      title={Test-Time Augmentation for 3D Point Cloud Classification and Segmentation},
      author={Tuan-Anh Vu, Srinjay Sarkar, Zhiyuan Zhang, Binh-Son Hua, Sai-Kit Yeung},
      booktitle={Proceedings of International Conference on 3D Vision (3DV)},
      year={2024}
    }
  

	@inproceedings{ziqiang2024coralscop,
		title={Coral{SCOP}: Segment any {CO}ral Image on this Planet},
		author={Ziqiang Zheng, Haixin Liang, Binh-Son Hua, Yue Him Wong, Put ANG Jr, Apple Pui Yi CHUI, Sai-Kit Yeung},
		booktitle={IEEE/CVF conference on Computer Vision and Pattern Recognition (CVPR)},
		year={2024},
	}