About Me

I am Peijun Bao. I received my Ph.D. from the Rose Lab at Nanyang Technological University, under the supervision of Prof. Alex Kot (SAEng/IEEE Life Fellow) and Prof. Er Meng Hwa (SAEng/IEEE Life Fellow). Previously, I received my master’s and bachelor’s degrees from Peking University and Northwestern Polytechnical University. My research interests lie in computer vision and machine learning.

News

[2024.08] Our ECCV paper is selected as an oral presentation!
[2024.07] 1 paper is accepted by ECCV 2024!
[2023.12] 2 papers are accepted by AAAI 2024!
[2022.12] 1 paper is accepted by AAAI 2023!
[2022.01] 1 paper is accepted by ICMR 2022!
[2021.01] 1 paper is accepted by AAAI 2021!

Publications

Peijun Bao, Anwei Luo, Alex Kot, Xudong Jiang
ActivityForensics: A Comprehensive Benchmark for Localizing Manipulated Activity in Videos,
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2026 [pdf], [code]

Zhaoxu Li, Chenqi Kong, Peijun Bao, Song Xia, Yi Tu, Yi Yu, Xinghao Jiang, Xudong Jiang
SAKED: Mitigating Hallucination in Large Vision-Language Models via Stability-Aware Knowledge Enhanced Decoding,
arxiv prerint, 2026 [pdf]

Chenqi Kong, Anwei Luo, Peijun Bao, Haoliang Li, Renjie Wan, Zengwei Zheng, Anderson Rocha, Alex Kot,
Open-set deepfake detection: a parameter-efficient adaptation method with forgery style mixture,
IEEE Transactions on Circuits and Systems for Video Technology (TCSVT), 2026 [pdf]

Peijun Bao, Chenqi Kong, Siyuan Yang, Zihao Shao, Xinghao Jiang, Boon Poh Ng, Menghwa Er, Alex Kot,
Vid-Group: Temporal Video Grounding Pretraining from Unlabeled Videos in the Wild,
International Conference on Computer Vision (ICCV), 2025 [pdf], [bib], [code]

Chenqi Kong, Anwei Luo, Peijun Bao, Yi Yu, Haoliang Li, Zengwei Zheng, Shiqi Wang, Alex Kot
Moe-ffd: Mixture of experts for generalized and parameter-efficient face forgery detection,
IEEE Transactions on Dependable and Secure Computing (TDSC), 2025 [pdf]

Peijun Bao, Zihao Shao, Wenhan Yang, Boon Poh Ng, Alex Kot,
E3M: Zero-Shot Spatio-Temporal Video Grounding with Expectation-Maximization Multimodal Modulation,
European Conference on Computer Vision (ECCV), 2024 (oral, top 2.4%) [pdf], [bib]

Peijun Bao, Zihao Shao, Wenhan Yang, Boon Poh Ng, Meng Hwa Er, Alex Kot,
Omnipotent Distillation with LLMs for Weakly-Supervised Natural Language Video Localization: When Divergence Meets Consistency,
Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024 [pdf], [bib]

Peijun Bao, Yong Xia, Wenhan Yang, Boon Poh Ng, Meng Hwa Er, Alex Kot,
Local-Global Multi-Modal Distillation for Weakly-Supervised Temporal Video Grounding,
Thirty-Eighth AAAI Conference on Artificial Intelligence (AAAI), 2024 [pdf], [bib]

Peijun Bao, Wenhan Yang, Boon Poh Ng, Meng Hwa Er, Alex Kot,
Cross-Modal Label Contrastive Learning for Unsupervised Audio-Visual Event Localization,
Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI), 2023 (oral) [pdf], [bib]

Peijun Bao, Yadong Mu,
Learning Sample Importance for Cross-Scenario Video Temporal Grounding,
The 12th International Conference on Multimedia Retrieval (ICMR), 2022 (oral) [pdf], [bib]

Peijun Bao, Qian Zheng, Yadong Mu,
Dense Events Grounding in Video,
Thirty-Fifth AAAI Conference on Artificial Intelligence (AAAI), 2021 (oral) [pdf], [bib], [code]
Note: we propose a popular new task i.e. Video Paragraph Grounding.
A list of works such as [CVPR24], [CVPR23], [CVPR22], [AAAI24], [ACM MM24], [CVIU24], and [EMNLP22] follow our task.

Chenchen Liu, Yongzhi Li, Kangqi Ma, Duo Zhang, Peijun Bao, Yadong Mu,
Learning 3-D Human Pose Estimation from Catadioptric Videos,
The 30th International Joint Conference on Artificial Intelligence (IJCAI), 2021 [pdf]

Runzhong Zhang, Fengrui Tian, Yueqi Duan, Chen Cai, Ziwei Wang, Weipeng Hu, Peijun Bao, Yang Chen, Suchen Wang, and Yap-Peng Tan
Learning Action Distribution Flow for Open-set Temporal Action Segmentation,
IEEE Transactions on Circuits and Systems for Video Technology (TIP), 2026 [pdf]