Biography [CV]
I am interested in video understanding, efficient architecture, multi-modality learning and generative AI. Most of my research is about video foundation model, including model design, large-scale pretraining, dataset collection and benchamrk evaluation.
Research
* refers to the co-first authors. Representative papers are
highlighted.
All my works are open-sourced on GitHub, and the full paper list can be found on
Google Scholar.
Internships
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OpenGVLab, Shanghai AI Lab, Shanghai, China
Nov. 2021 – Present
Research Intern
Advisor: Yali Wang, Limin Wang, Yi Wang
Topic: General Video Foundation Model; Large-scale Pre-training; Multimodal Learning
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X-Lab, SenseTime, Beijing, China
Feb. 2021 – Nov. 2021
Research Intern
Advisor: Guanglu Song, Yu Liu
Topic: Efficient Architecture Design; Video Understanding
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Megvii, Beijing, China
Oct. 2019 – Jan. 2020
Research Intern
Topic: Model Reproduction for MegEngine
Honors
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Top 10 Outstanding Graduate Students in SIAT, UCAS
2023
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National award scholarship
2023
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Dean Scholarship of University of Chinese Academy of Sciences
2022, 2023
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Merit Student at University of Chinese Academy of Sciences
2021, 2022
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1st Place in Forecasting Challenge (ECCV2022 Ego4D Workshop)
2022
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2nd Place in Action Recognition in the Dark Challenge (CVPR2022 UG2+ Workshop)
2022
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1st Place in Semantic Segmentation of Remote Sensing Images (CCF BDCI Contest)
2021
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Comprehensive Grand Prize of CCF BDCI Contest
2021
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Excellent Higher Education Graduate of Beijing Municipality
2020
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Grand Prize of Social Work Scholarship, Grand Prize of Study Excellence Scholarship,
Merit Student and
Honor student at Beihang University
2017, 2018, 2019
Services
- Conference Reviewer: ICLR2023/2024/2025, CVPR2023/2024, ICCV2023, NeurIPS2023/2024, ICML2024, ECCV2024
- Journal Reviewer: TPAMI, IJCV, PR, NN, JVCI
- Talk: AI Drive 2022, AI Time 2022, AI Time 2023, others (FDU, UCAS, KAUST...)
© Kunchang Li | Last updated: 08/01/2024