Chenguo Lin

👤 Biography

Hi there👋, my name is Chenguo Lin (in Chinese: 林琛果). I am a third-year Ph.D. student of computer science and artificial intelligence at Peking University, China, supervised by Prof. Yadong Mu. My recent research interest is in generative models and multi-modal representation learning, especially in the 3D domain. Currently, I'm working as a research intern at PICO, ByteDance, focusing on 3D AIGC. I've spent wonderful time as a research assistant/intern with Dr. Zhirong Wu at Microsoft Research Asia, Prof. Ping Luo at HKU, and Dr. Chaoning Zhang at KAIST.

I'm always open to research discussions and collaborations. Feel free to contact me if you are interested.

📢 News

• [2024-09] One paper about generalizable single-view human reconstruction (HumanSplat) was accepted to NeurIPS 2024
• [2024-07] One paper about large-scale time-series pretraining (NuTime) was accepted to TMLR 2024
• [2024-01] One paper about 3D scene synthesis (InstructScene) was accepted to ICLR 2024 as a spotlight paper.

📑 Selected Publications [Google Scholar]

*: equal contribution

NeurIPS 2024	HumanSplat: Generalizable Single-Image Human Gaussian Splatting with Structure Priors Panwang Pan*, Zhuo Su*, Chenguo Lin*, Zhen Fan, Yongjie Zhang, Zeming Li, Tingting Shen, Yadong Mu, Yebin Liu Neural Information Processing Systems (NeurIPS), 2024 [OpenReview] [arXiv] [Project Page] [Code] TL;DR: HumanSplat predicts the 3D Gaussian Splatting properties of any human from a single input image in seconds.
arXiv 2024	InstructLayout: Instruction-Driven 2D and 3D Layout Synthesis with Semantic Graph Prior Chenguo Lin*, Yuchen Lin*, Panwang Pan, Xuanyang Zhang, Yadong Mu Preprint (arXiv), 2024 Under review by Transactions on Pattern Analysis and Machine Intelligence (T-PAMI) [arXiv] TL;DR: InstructLayout is an extension of InstructScene that improves controllability and fidelity for the layout synthesis of both 2D E-commerce posters and 3D indoor scenes.
ICLR 2024	InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior Chenguo Lin, Yadong Mu International Conference on Learning Representations (ICLR), 2024 Spotlight (acceptance rate: 5%) [OpenReview] [arXiv] [Project Page] [Code] TL;DR: InstructScene is a generative framework to synthesize 3D indoor scenes from instructions, and is composed of a semantic graph prior and a layout decoder.
TMLR 2024	NuTime: Numerically Multi-Scaled Embedding for Large-Scale Time-Series Pretraining Chenguo Lin*, Xumeng Wen*, Wei Cao, Congrui Huang, Jiang Bian, Stephen Lin, Zhirong Wu Transactions on Machine Learning Research (TMLR), 2024 [OpenReview] [arXiv] [Code] TL;DR: NuTime is a Transformer-based architecture that can take raw values of time-series data as input without any data normalization and transformation.

💼 Experiences

• PICO, ByteDance
  December 2023 - present
  
  Research Intern
  Collaborators: Panwang Pan, Bangbang Yang, Zhuo Su, Zeming Li
  Topic: Generative Models for 3D Content
• Microsoft Research Asia (MSRA)
  November 2021 - September 2022
  
  Research Intern
  Mentor: Dr. Zhirong Wu
  Topic: Time-Series Self-supervised Representation Learning
• The University of Hong Kong (HKU)
  June 2021 - August 2021
  
  Research Assistant
  Advisor: Prof. Ping Luo
  Topic: Neural Architecture Search
• Korea Advanced Institute of Science and Technology (KAIST)
  December 2020 - May 2021
  
  Research Assistant
  Advisor: Dr. Chaoning Zhang
  Topic: Deep Data Hiding, Adversarial Attack

🎓 Educations

• Ph.D. student, School of Intelligence Science and Technology, Peking University
  2022 - present
  
  
• B.Eng., College of Computer Science, Sichuan University
  2018 - 2022
  
  
  • Comprehensive Ranking: 1/171
  • Member of Honor College (for top 2% undergraduates at Sichuan University)

🏆 Honors & Awards

• Fresh Ph.D. Student Scholarship of WICT, Peking University (only 4 winners at WICT per year)
  2022
• Outstanding Bachelor Thesis, Sichuan University
  2022
• BaoSteel Scholarship, BaoSteel Education Foundation (only 6 winnners in SCU per year, including postgraduates)
  2021
• National Scholarship, Ministry of Education (the highest honor scholarship in China)
  2021
• Outstanding Graduate, Sichuan University
  2021
• Outstanding Student (Cadre), Sichuan University
  2021,2020,2019
• Comprehensive Scholarship, Sichuan University
  2021, 2020, 2019

📝 Services

• Conference Reviewer: ICCV 2023, NeurIPS 2023-2024, ICLR 2024-2025, ICML 2024
• Journal Reviewer: TPAMI, TMM