Guodong Ding's Homepage
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Guodong Ding (Ph.D) 丁国栋 [CV]
dinggd [at] comp.nus.edu [dot] sg |
Research Interest
My research focuses on understanding human actions in long-range, multi-step video sequences, particularly temporal action segmentation. Recently, my work has expanded to explore efficient understanding of procedural videos in continual and online settings.
Updates
[Feb., 25] One conference paper on condensing action segmentation datasets accepted to CVPR2025.
[Jan., 25] We will be organizing Workshop on vision-based assistant in real-world at CVPR2025.
[Oct., 24] I gave a talk on Unraveling Actions in Procedural Videos at NUS Lunch Meida Talk.
[Sep., 24] One conference paper on online action segmentation accepted to NeurIPS2024, congrats to Qing!
[Jun., 24] I serve as Senior Program Committee for AAAI2024.
[Apr., 24] One extended abstract on detecting procedural mistakes accepted to CVPR2024 Workshop LPVL2024.
[Feb., 24] One conference paper on incremental action segmenation accepted to CVPR2024.
[Jan., 24] One survey paper accpeted to TPAMI.
Employment
Senior Research Fellow (Oct., 23 - Present), in School of Computing (SoC), National University of Singapore, Singapore.
Research Fellow (Oct., 20 - Oct., 23), in School of Computing (SoC), National University of Singapore, Singapore.
Research Intern (June, 19 - Sept., 19), in China QCT MM R&D, Qualcomm Shanghai, China.
Research Experiences
Visiting Scholar (Feb., 17 - Oct., 17), in Australian National University, Australia.
Research Assistant (Nov., 15 - Feb., 17), in the Hong Kong Polytechnic University, Hong Kong, China.
Adivsed Students
Hang Guo (2025, Master, Tsinghua Univeristy)
Alberto Mate (2024, Master, Universitat Politècnica de Catalunya)
Qing Zhong (2024, PhD, University of Adelaide)
Hans Golong (2023 - 2024, Master, National University of Singapore)
Publications
[Google Scholar] (*: corresponding author, underlined: supervised student)
Conference papers
G. Ding, R. Chen and A. Yao, “Condensing Action Segmentation Datasets via Generative Network Inversion,” Computer Vision and Pattern Recognition 2025. [pdf]|[project page]|[poster]
Q. Zhong, G. Ding, and A. Yao, “OnlineTAS: An Online Baseline for Temporal Action Segmentation,” Conference on Neural Information Processing Systems 2024. [pdf]|[project page]
G. Ding, F. Sener, S. Ma and A. Yao, “Ordering Mistake Detection in Assembly Tasks,” CVPR Workshop 2024. [pdf]|[project page]|[annots]
G. Ding, H. Golong and A. Yao, “Coherent Temporal Synthesis for Incremental Action Segmentation,” Computer Vision and Pattern Recognition 2024. [project page]|[pdf]|[video]|[supp]|[poster]|[slides]
G. Ding and A. Yao, “Leveraging Action Affinity and Continuity for Semi-supervised Temporal Action Segmentation,” European Conference on Computer Vision 2022. [project page]| [pdf]|[video]|[poster]
G. Ding, S. Khan, and Z. Tang, “Dispersion-based Clustering for Unsupervised Person Re-identification,” British Machine Vision Conference, 2019. [pdf]|[project page]
G. Ding*, S. Zhang, S. Khan, and Z. Tang, “Center based Pseudo-labeling for Semi-supervised Person Re-identification,” International Conference of Multimedia and Expo Workshops 2018. [pdf]|[slides]
Journal articles
G. Ding, F. Sener and A. Yao, “Temporal Action Segmentation: An Analysis of Modern Techniques,” IEEE Transactions on Pattern Analysis and Machine Intelligence 2023. [pdf]|[project page]|[resources]
G. Ding and A. Yao, “Temporal Action Segmentation with High-level Complex Activity Labels,” IEEE Transcations on Multimedia 2022. [pdf]|[project page]
Q. Yin, G. Wang, G. Ding, Q. Li, S. Gong and Z. Tang, “Rapid Person Re-Identification via Sub-space Consistency Regularization,” Neural Processing Letters 2022. [pdf]|[project page]
Q. Yin, G. Wang, G. Ding, S. Gong and Z. Tang, “Multi-View Label Prediction for Unsupervsied Person Re-identification,” IEEE Singal Processing Letters 2021. [pdf]|[project page]
G. Ding*, S. Zhang, S. Khan, Z. Tang, J. Zhang and F. Porikli, “Feature Affinity based Pseudo Labeling for Semi-supervised Person Re-identification,” IEEE Transcations on Multimedia 2019. [pdf]|[project page]
G. Ding*, S. Khan, Z. Tang, and F. Porikli, “Feature Mask Network for Person Re-identification,” Pattern Recognition Letters 2019. [pdf]|[project page]
Preprints
G. Ding*, S. Khan, Z. Tang, J. Zhang and F. Porikli, Towards better Validity: Dispersion based Clustering for Unsupervised Person Re-identification, Arxiv paper 2019. [pdf]|[code]|[project page]
Talks
“Unraveling Actions in Procedural Activities”, Media Talk at NUS.
Reviewer
Journal:
IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI)
IEEE Transactions on Multimedia (TMM)
IEEE Transactions on Image Processing (TIP)
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT)
ACM Transactions on Sensor Networks (TOSN)
IEEE Transactions on Industrial Informatics (TII)
Conference:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (2021 - 2024)
European Conference on Computer Vision (ECCV) (2020, 2022, 2024)
IEEE/CVF International Conference on Computer Vision (ICCV) (2021, 2023)
Advances in Neural Information Processing Systems (NeurIPS) (2023 - 2024)
AAAI Conference on Artificial Intelligence (AAAI) (2023 - 2024)
British Machine Vision Conference (BMVC) (2020 - 2024)
Service
Workshop (VAR) Oragnizer, CVPR 2025.
Area Chair (SPC), AAAI 2025.
Tutorial (ATLAS) Organizer, ECCV 2022.
Collaborators
Prof. Angela Yao, School of Computing, National University of Singapore
Dr. Fadime Sener, Reality Labs Research, Meta
Prof. Salman Khan, MBZUAI & Australian National University
Prof. Jian Zhang, University of Technology Sydney
Prof. Fatih Porikli, Qualcomm, USA
Prof. Shanshan Zhang, Nanjing University of Science and Technology
