Guosheng Lin

Assistant Professor

Block N4, 02b-64, 
School of Computer Science and Engineering,
Nanyang Technological University, Singapore.
E-mail:   gslin{At}ntu.edu.sg   or   guosheng.lin{At}gmail.com


I occasionally have openings for interns, research assistants and PhD students. 
If you are interested, please email me with your CV for enquiries.

My research interests are in machine learning and computer vision applications, particularly in visual recognition problems.
Before moving to NTU Singapore, I was a research fellow at Australian Centre for Robotic Vision (ACRV) and Australian Centre for Visual Technologies (ACVT),  
I completed my PhD degree at the University of Adelaide (2010-2014), supervised by Prof. Chunhua Shen (principal),  Prof. David Suter and Dr.Tat-Jun Chin
I received my bachelor and master degree from South China University of Technology (SCUT) in 2007 and 2010 respectively.

Google scholar page: [link]

Awards
:

Google PhD fellowship, Australia, 2014, see here or here.

Teaching:

Working papers:


Conference publications:

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  •  "RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation";
Guosheng Lin, Anton Milan, Chunhua Shen, Ian Reid; IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017; [arXiv]

Top performance on PASCAL VOC 2012 dataset (Links: Leaderboard),
**NEW**  our source code and trained models are available at: https://github.com/guosheng/refinenet
(MATLAB based framework for semantic segmentation and dense preidction)
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  •  "Sequential Person Recognition in Photo Albums with a Recurrent Network";
Yao Li, Guosheng Lin, Bohan Zhuang, Lingqiao Liu, Chunhua Shen, Anton van den Hengel; IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017; [arXiv]
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  • Weakly Supervised Semantic Segmentation Based on Co-segmentation
Tong Shen, Guosheng Lin, Lingqiao Liu, Chunhua Shen, Ian Reid; The British Machine Vision Conference (BMVC) 2017; [arXiv]
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  • Learning Multi-level Region Consistency with Dense Multi-label Networks for Semantic Segmentation
Tong Shen*, Guosheng Lin*, Chunhua Shen, Ian Reid; International Joint Conference on Artificial Intelligence (IJCAI) 2017; [arXiv]
( * indicates equal contribution );
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  • "Efficient Piecewise Training of Deep Structured Models for Semantic Segmentation"
Guosheng Lin,  Chunhua Shen, Anton van den Hengel, Ian Reid; IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016, Spotlight presentation; [arXiv]

Links: PASCAL VOC 2012 dataset Leaderboard, Cityscapes dataset Leaderboard.
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  • "Fast training of triplet-based deep binary embedding networks "
Bohan Zhuang, Guosheng Lin,  Chunhua Shen, Ian Reid; IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016; [arXiv]
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  • "Deeply Learning the Messages in Message Passing Inference"
Guosheng Lin,  Chunhua Shen, Ian Reid, Anton van den Hengel;  Advances in Neural Information Processing Systems (NIPS), 2015, [arXiv]
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  • "Deep Convolutional Neural Fields for Depth Estimation from a Single Image"
Fayao Liu, Chunhua Shen, Guosheng Lin; IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015; [arXiv]

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  • "Sequence Searching With Deep-Learnt Depth for Condition and Viewpoint-Invariant Route-Based Place Recognition"
Michael Milford, Chunhua Shen, Stephanie Lowry, Niko Suenderhauf, Sareh Shirazi, Guosheng Lin, Fayao Liu,
Edward Pepperell, Cesar Lerma, Ben Upcroft, Ian Reid; The 6th international Workshop on Computer Vision in Vehicle Technology, CVPR2015 workshop.
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  • "Fast Supervised Hashing with Decision Trees for High-Dimensional Data";
Guosheng Lin, Chunhua Shen, Qinfeng Shi, Anton van den Hengel and David Suter; IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2014; [PDF]

Code: https://bitbucket.org/chhshen/fasthash/
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  • "Optimizing Ranking Measures For Compact Binary Code Learning"
Guosheng Lin,  Chunhua Shen, Jianxin Wu; European Conference on Computer Vision (ECCV), 2014; [PDF]

Extensions of this method for efficient training are also included
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  • "A General Two-Step Approach to Learning-Based Hashing";
Guosheng Lin, Chunhua Shen, David Suter and Anton van den Hengel; International Conference on Computer Vision  (ICCV), 2013; [PDF] or [PDF]

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  •  "Learning Hash Functions Using Column Generation";
Xi Li*, Guosheng Lin*, Chunhua Shen, Anton van den Hengel and Anthony Dick; International Conference on Machine Learning (ICML), 2013; Oral Presentation; [PDF]
 ( * indicates equal contribution );

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  • "Approximate Constraint Generation for Efficient Structured Boosting";
Guosheng Lin, Chunhua Shen and Anton van den Hengel; International Conference on Image Processing (ICIP), 2013; [PDF] or [PDF]
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  • "Fast Training of Effective Multi-class Boosting Using Coordinate Descent Optimization";
Guosheng Lin, Chunhua Shen, Anton van den Hengel and David Suter;  Asian Conference on Computer Vision (ACCV), 2012; [PDF] or [PDF]

Code: https://bitbucket.org/guosheng/fast-multiboost-cw
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Journal publications:


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  • "Exploring Context with Deep Structured models for Semantic Segmentation";
Guosheng Lin, Chunhua Shen, Anton van den Hengel, Ian Reid;  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2017; [PDF]
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  • "Supervised Hashing Using Graph Cuts and Boosted Decision Trees";
Guosheng Lin, Chunhua Shen, Anton van den Hengel;  IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2015; [PDF] or [arXiv]

Code: https://bitbucket.org/chhshen/fasthash/
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  • "Structured Learning of Binary Codes with Column Generation for Optimizing Ranking Measures"
Guosheng Lin, Fayao Liu, Chunhua Shen, Jianxin Wu, Heng Tao Shen; International Journal of Computer Vision (IJCV); 2017; [PDF]

Code: https://bitbucket.org/guosheng/structhash
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  • "Learning Depth from Single Monocular Images Using Deep Convolutional Neural Fields"
Fayao Liu, Chunhua Shen, Guosheng Lin, Ian Reid; IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI); 2016; [arXiv] or [PDF]

Code: https://bitbucket.org/fayao/dcnf-fcsp/
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  • "StructBoost: Boosting Methods For Predicting Structured Output Variables";
Chunhua Shen, Guosheng Lin, Anton van den Hengel; IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014; [PDF] or [arXiv]

The following code provides the implementation of cutting-plane and an example of column generation:
https://bitbucket.org/guosheng/structhash
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  • Discriminative Training of Deep Fully-connected Continuous CRF with Task-specific Loss
Fayao Liu, Guosheng Lin, Chunhua Shen; IEEE Transactions on Image Processing (TIP), 2017; [PDF]
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  • Structured Learning of Tree Potentials in CRF for Image Segmentation
Fayao Liu, Guosheng Lin, Ruizhi Qiao, Chunhua Shen; IEEE Transactions on Neural Networks and Learning Systems (TNNLS), 2017; [PDF]
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  •  "CRF Learning with CNN Features for Image Segmentation";
Fayao Liu, Guosheng Lin, Chunhua Shen; Pattern Recognition (PR), 2015; [PDF]
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  • Crowd Counting via Weighted VLAD on Dense Attribute Feature Maps
Biyun Sheng, Chunhua Shen, Guosheng Lin, Jun Li, Wankou Yang, Changyin Sun; IEEE Transactions on Circuits and Systems for Video Technology (T-CSVT); 2016; [PDF]
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