Shoubin Yu

Shoubin Yu

UNC, Chapel Hill

Hi, thanks for stopping by! I am now a second-year Ph.D. Student at The University of North Carolina at Chapel Hill, advised by Prof. Mohit Bansal. Previously, I did my undergraduate study at Shanghai Jiao Tong University.

While at UNC, I spent my summer time at Adobe Research (2024), Amazon Alexa (2023). Prior to UNC, I did research projects at SenseTime Research (2021), and with MIT-IBM Watson AI Lab (2021).

I am interested in wide topics in computer vision, especially in video, including video+X (language, audio, robotics) understanding & generation, trustworthy video reasoning, and robust video representation learning.

Find me here: shoubin -atsign- cs . unc . edu

ðŸ”Ĩ News

  • 2024.07: ðŸ“đ One paper accepted to ACM MM 2024. Check IVA-0 for controllable image animation.
  • 2024.06: 💎 Gave an invited talk at Google.
  • 2024.05: 🎎 Start summer intern at Adobe as Research Scientist.
  • 2023.09: ⛓ïļ One paper accepted to NeurIPS 2023. Check SeViLA for Video Loc+QA.
  • 2023.07: ðŸĶī One paper accepted to IEEE TCSVT. Check MoPRL for skeletal anomaly detection.
  • 2023.05: 🌞 Start summer intern at Amazon as Research Scientist.
  • 2022.09: ⛩ïļ Join UNC-CH MURGe-Lab .
  • 2022.06: 🎓 Graduate from Shanghai Jiao Tong University (excellent graduates).
  • 2021.10: 🌟 One paper accepted to NeurIPS 2021. Check STAR for real-world situated reasoning.

📝 Pre-print (*: equal contribution/co-first author)

Preprint
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VideoTree: Adaptive Tree-based Video Representation for LLM Reasoning on Long Videos

Ziyang Wang*, Shoubin Yu*, Elias Stengel-Eskin*, Jaehong Yoon, Feng Cheng, Gedas Bertasius, Mohit Bansal

Code | Project Page

  • We present VideoTree, an adaptive tree-based video presentation/prompting with simple visual clusturing for long video reasoning with LLM.
Preprint
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RACCooN: Remove, Add, and Change Video Content with Auto-Generated Narratives

Jaehong Yoon*, Shoubin Yu*, Mohit Bansal

Code | Project Page

  • We present RACCooN, a versatile and user-friendly video-to-paragraph-to-video framework, enables users to remove, add, or change video content via updating auto-generated narratives.
Preprint
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CREMA: Generalizable and Efficient Video-Language Reasoning via Multimodal Modular Fusion

Shoubin Yu*, Jaehong Yoon*, Mohit Bansal

Code | Project Page

  • We present CREMA, an efficient & modular modality-fusion framework for injecting any new modality into video reasoning.
Preprint
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A Simple LLM Framework for Long-Range Video Question-Answering

Ce Zhang, Taixi Lu, Md Mohaiminul Islam, Ziyang Wang, Shoubin Yu, Mohit Bansal, Gedas Bertasius

Code

  • We present LLoVi, a simple yet effective framework with LLM for long-range video question-answering.

📝 Publications

ACM MM 2024
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Zero-Shot Controllable Image-to-Video Animation via Motion Decomposition

Shoubin Yu, Jacob Zhiyuan Fang, Skyler Zheng, Gunnar Sigurdsson, Vicente Ordonez, Robinson Piramuthu, Mohit Bansal

(To appear) Code | Homepage

  • We present IVA-0, a Image-to-Video animationor, enables precise control from users through in-place and out-of-place motion decomposition.
NeurIPS 2023
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Self-Chained Image-Language Model for Video Localization and Question Answering

Shoubin Yu, Jaemin Cho, Prateek Yadav, Mohit Bansal

Code | Demo | Talk

  • We propose SeViLA, which self-chained BLIP-2 for 2-stage video question-answering (localization + QA) & refine localization with QA feedback.
TCSVT 2023
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Regularity Learning via Explicit Distribution Modeling for Skeletal Video Anomaly Detection

Shoubin Yu, Zhongyin Zhao, Haoshu Fang, Andong Deng,Haisheng Su, Dongliang Wang, Weihao Gan, Cewu Lu, Wei Wu

Code

  • We propose MoPRL, a transformer-based model incorporated with skeletal motion prior for efficient video anomaly detection.
NeurIPS 2021
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STAR: A Benchmark for Situated Reasoning in Real-World Videos

Bo Wu, Shoubin Yu, Zhenfang Chen, Joshua B. Tenenbaum, Chuang Gan

Code | Project Page

  • We propose STAR, a benchmark for neural-symbolic video reasoning in real-world scenes.

🎖 Honors and Awards

  • CN Patent CN114724062A, 2022
  • The Hui-Chun Chin and Tsung Dao Lee Scholar, 2020
  • CN Patent CN110969107A, 2019
  • Meritorious Award in Mathematical Contest in Modeling, 2019
  • Second Prize in Shanghai, China Undergraduate Mathematical Contest in Modeling, 2019

🧐 Service

  • Conference reviewer: CVPR, ECCV, NeurIPS, ACL, EACL, CoNLL, AAAI
  • Journal reviewer: IEEE Transactions on Circuits and Systems for Video Technology

📖 Educations

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  • 2022.09 - Present
  • The University of North Carolina at Chapel Hill
  • Computer Science, Ph.D.
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  • 2017.09 - 2022.06
  • Shanghai Jiao Tong University
  • Information Security, B.Eng.

ðŸ’ŧ Internships

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