World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
50
Citations
16169
World Ranking
5488
National Ranking
77

Overview

Guosheng Lin is affiliated with Nanyang Technological University in Singapore and has a substantial body of research within the fields of Computer Science and Engineering. Their work predominantly focuses on Computer Vision and Pattern Recognition, alongside significant contributions to Artificial Intelligence, Computational Mechanics, Computer Graphics and Computer-Aided Design, and Geology.

Their research spans several main topics, including:

  • 3D Shape Modeling and Analysis
  • Domain Adaptation and Few-Shot Learning
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Advanced Image and Video Retrieval Techniques
  • Advanced Vision and Imaging
  • Human Pose and Action Recognition

Guosheng Lin has authored numerous publications, frequently contributing to journals and conferences such as arXiv (Cornell University), IEEE Transactions on Pattern Analysis and Machine Intelligence, International Journal of Computer Vision, SSRN Electronic Journal, and IEEE Transactions on Multimedia.

Their recent notable papers include:

  • Video Object Segmentation and Tracking, 2020, ACM Transactions on Intelligent Systems and Technology
  • Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • Learning Meta-class Memory for Few-Shot Semantic Segmentation, 2021, 2021 IEEE/CVF International Conference on Computer Vision (ICCV)
  • A Unified Transformer Framework for Group-Based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object Detection, 2023, IEEE Transactions on Multimedia
  • DeepEMD: Differentiable Earth Mover's Distance for Few-Shot Learning, 2022, IEEE Transactions on Pattern Analysis and Machine Intelligence

Collaboration has been a significant aspect of Guosheng Lin's research, with frequent co-authors including Fayao Liu, Qingyao Wu, Zhiguo Cao, Weide Liu, and Zhonghua Wu. These partnerships have contributed to a diverse and robust research portfolio.

Best Publications

  • RefineNet: Multi-path Refinement Networks for High-Resolution Semantic Segmentation

    Guosheng Lin;Anton Milan;Chunhua Shen;Ian Reid

  • Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields

    Fayao Liu;Chunhua Shen;Guosheng Lin;Ian Reid

  • Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation

    Guosheng Lin;Chunhua Shen;Anton van den Hengel;Ian Reid

  • Deep convolutional neural fields for depth estimation from a single image

    Fayao Liu;Chunhua Shen;Guosheng Lin

  • DeepEMD: Few-Shot Image Classification With Differentiable Earth Mover’s Distance and Structured Classifiers

    Chi Zhang;Yujun Cai;Guosheng Lin;Chunhua Shen

  • CANet: Class-Agnostic Segmentation Networks With Iterative Refinement and Attentive Few-Shot Learning

    Chi Zhang;Guosheng Lin;Fayao Liu;Rui Yao

  • Fast Supervised Hashing with Decision Trees for High-Dimensional Data

    Guosheng Lin;Chunhua Shen;Qinfeng Shi;Anton van den Hengel

  • Pyramid Graph Networks With Connection Attentions for Region-Based One-Shot Semantic Segmentation

    Chi Zhang;Guosheng Lin;Fayao Liu;Jiushuang Guo

  • Few-Shot Incremental Learning with Continually Evolved Classifiers

    Chi Zhang;Nan Song;Guosheng Lin;Yun Zheng

  • CRNet: Cross-Reference Networks for Few-Shot Segmentation

    Weide Liu;Chi Zhang;Guosheng Lin;Fayao Liu

  • CRF learning with CNN features for image segmentation

    Fayao Liu;Guosheng Lin;Chunhua Shen

  • Video Object Segmentation and Tracking: A Survey

    Rui Yao;Guosheng Lin;Shixiong Xia;Jiaqi Zhao

  • A General Two-Step Approach to Learning-Based Hashing

    Guosheng Lin;Chunhua Shen;David Suter;Anton Van Den Hengel

  • Progressive Modality Reinforcement for Human Multimodal Emotion Recognition from Unaligned Multimodal Sequences

    Fengmao Lv;Xiang Chen;Yanyong Huang;Lixin Duan

  • Exploring Context with Deep Structured Models for Semantic Segmentation

    Guosheng Lin;Chunhua Shen;Anton van den Hengel;Ian Reid

  • A Dilated Inception Network for Visual Saliency Prediction

    Sheng Yang;Guosheng Lin;Qiuping Jiang;Weisi Lin

  • MoNet: Deep Motion Exploitation for Video Object Segmentation

    Huaxin Xiao;Jiashi Feng;Guosheng Lin;Yu Liu

  • Multi-Path Region Mining for Weakly Supervised 3D Semantic Segmentation on Point Clouds

    Jiacheng Wei;Guosheng Lin;Kim-Hui Yap;Tzu-Yi Hung

  • Context Decoupling Augmentation for Weakly Supervised Semantic Segmentation

    Yukun Su;Ruizhou Sun;Guosheng Lin;Qingyao Wu

  • Learning Hash Functions Using Column Generation

    Xi Li;Guosheng Lin;Chunhua Shen;Anton Van den Hengel

  • RefineNet: Multi-Path Refinement Networks for Dense Prediction

    Guosheng Lin;Fayao Liu;Anton Milan;Chunhua Shen

  • Fast Training of Triplet-Based Deep Binary Embedding Networks

    Bohan Zhuang;Guosheng Lin;Chunhua Shen;Ian Reid

  • Learning Markov Clustering Networks for Scene Text Detection

    Zichuan Liu;Guosheng Lin;Sheng Yang;Jiashi Feng

Frequent Co-Authors

Chunhua Shen
Chunhua Shen Zhejiang University
Ian Reid
Ian Reid University of Adelaide
Anton van den Hengel
Anton van den Hengel University of Adelaide
Jianfei Cai
Jianfei Cai Monash University
Steven C. H. Hoi
Steven C. H. Hoi Alibaba Group (China)
Weisi Lin
Weisi Lin Nanyang Technological University
Lingqiao Liu
Lingqiao Liu University of Adelaide
David Suter
David Suter Edith Cowan University
Chunyan Miao
Chunyan Miao Nanyang Technological University
Qinfeng Shi
Qinfeng Shi University of Adelaide

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