I received my Ph.D. from Dalian University of Technology, advised by Prof. Peihua Li. My research focuses on computer vision, with particular interests in multimodal large language models, video understanding, image recognition, few-shot learning, and representation learning.
My work has been published in leading conferences and journals, including CVPR, NeurIPS, IJCV, ACM MM, and IEEE TNNLS.
I have served as a reviewer for CVPR, ICCV, IJCV, TIP, TNNLS, AAAI, and ACM MM.
I am currently seeking research and engineering opportunities in computer vision, multimodal learning, and foundation models.
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Dalian University of TechnologySignal and Information ProcessingPh.D.Sep. 2019 - Sep. 2025 -
Dalian University of TechnologyInformation and Communication EngineeringM.S.Sep. 2017 - Jun. 2019
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Nanjing Agricultural UniversityElectronic Information Science and TechnologyB.S.Sep. 2013 - Jun. 2017
Experience
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The Hong Kong Polytechnic UniversityResearch AssistantComputer Vision ResearchNov. 2018 - May 2019 -
Alibaba DAMO AcademyResearch InternComputer Vision ResearchApr. 2019 - Jul. 2019
Academic Service
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Reviewer for CVPR, ICCV, IJCV, TIP, TNNLS, AAAI, and ACM MM
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Teaching Assistant for the graduate-level Computer Vision course, Dalian University of Technology, 2020-2021
Honors & Awards
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CVPR 2025 Outstanding Reviewer2025
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Special Scholarship for Outstanding Doctoral Dissertation, Dalian University of Technology (10 recipients university-wide)2024
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Outstanding Doctoral Dissertation Scholarship, Dalian University of Technology (20 recipients university-wide)2023
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Academic Star Nomination Award, Dalian University of Technology2021
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CVPR 2017 Workshop iNaturalist Challenge, Fine-Grained Visual Categorization, 5th / 50 [web]2017
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Mathematical Contest in Modeling (MCM/ICM), Meritorious Winner2015
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China Undergraduate Mathematical Contest in Modeling, Second Prize2014
Talks & Presentations
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NeurIPSPosterVirtual2021
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Machine Learning and Applications Workshop (MLA)SpotlightTianjin2019
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Chinese Conference on Pattern Recognition and Computer Vision (PRCV)PosterGuangzhou2018
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Vision and Learning Seminar (VALSE)PosterDalian2018
Selected Publications (view all )
A2M2-Net: Adaptively Aligned Multi-Scale Moment for Few-Shot Action Recognition
Zilin Gao*, Qilong Wang*, Bingbing Zhang, Qinghua Hu, Peihua Li (* equal contribution)
In International Journal of Computer Vision (IJCV) 2025
We propose an adaptively aligned multi-scale moment framework for few-shot action recognition, addressing temporal misalignment through hierarchical spatio-temporal moment modeling and interactive matching.
A2M2-Net: Adaptively Aligned Multi-Scale Moment for Few-Shot Action Recognition
Zilin Gao*, Qilong Wang*, Bingbing Zhang, Qinghua Hu, Peihua Li (* equal contribution)
In International Journal of Computer Vision (IJCV) 2025
We propose an adaptively aligned multi-scale moment framework for few-shot action recognition, addressing temporal misalignment through hierarchical spatio-temporal moment modeling and interactive matching.
TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition
Yilong Wang*, Zilin Gao*, Qilong Wang, Zhaofeng Chen, Peihua Li, Qinghua Hu (* equal contribution)
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025
A temporal-aware model tuning method for cross-domain few-shot action recognition that improves adaptation under domain shift.
TAMT: Temporal-Aware Model Tuning for Cross-Domain Few-Shot Action Recognition
Yilong Wang*, Zilin Gao*, Qilong Wang, Zhaofeng Chen, Peihua Li, Qinghua Hu (* equal contribution)
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2025
A temporal-aware model tuning method for cross-domain few-shot action recognition that improves adaptation under domain shift.
Temporal-Attentive Covariance Pooling Networks for Video Recognition
Zilin Gao, Qilong Wang, Bingbing Zhang, Peihua Li
In Advances in Neural Information Processing Systems (NeurIPS) 2021
We introduce temporal-attentive covariance pooling for video recognition, jointly modeling intra-frame and inter-frame relationships with calibrated covariance representations.
Temporal-Attentive Covariance Pooling Networks for Video Recognition
Zilin Gao, Qilong Wang, Bingbing Zhang, Peihua Li
In Advances in Neural Information Processing Systems (NeurIPS) 2021
We introduce temporal-attentive covariance pooling for video recognition, jointly modeling intra-frame and inter-frame relationships with calibrated covariance representations.
Global Second-Order Pooling Convolutional Networks
Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2019 600+ citations
We develop a plug-and-play global second-order pooling module for visual recognition by explicitly modeling channel correlations with covariance representations.
Global Second-Order Pooling Convolutional Networks
Zilin Gao, Jiangtao Xie, Qilong Wang, Peihua Li
In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2019 600+ citations
We develop a plug-and-play global second-order pooling module for visual recognition by explicitly modeling channel correlations with covariance representations.
Global Gated Mixture of Second-Order Pooling for Improving Deep Convolutional Neural Networks
Qilong Wang*, Zilin Gao*, Jiangtao Xie, Wangmeng Zuo, Peihua Li (* equal contribution)
In Advances in Neural Information Processing Systems (NeurIPS) 2018
A gated mixture of second-order pooling approach for improving deep convolutional neural networks.
Global Gated Mixture of Second-Order Pooling for Improving Deep Convolutional Neural Networks
Qilong Wang*, Zilin Gao*, Jiangtao Xie, Wangmeng Zuo, Peihua Li (* equal contribution)
In Advances in Neural Information Processing Systems (NeurIPS) 2018
A gated mixture of second-order pooling approach for improving deep convolutional neural networks.