About Me
Hi, there! I am Shunlin Lu, a first-year Ph.D. student affiliated at School of Data Scienec (SDS), The Chinese University of Hongkong (Shenzhen). I am honored to be co-supervised by Prof. Ruimao Zhang and Prof. Benyou Wang. Previously, I obtained my master's degree from University of Southern California (USC) and bachelor's degree from Wuhan University of Technology. Recently, my research interests mainly lie in Multi-Modal LLMs, Character Animation, Motion Generation/Understanding, and Machine Learning. When I was in USC, I worked closely with Dr. Souvik Kundu (Intel AI lab). I had a wonderful time as a research intern at the International Digital Economy Academy (IDEA), working closely with Dr. Ailing Zeng and Prof. Lei Zhang. Now, I'm a research intern at Shanghai AI lab, working with Dr. Jingbo Wang. My reseach goal is to build a generalizable and robust animation system to serve for embodied intelligence and virtual entertainment.
News
- One paper was accepted to ICML (2024).
- One paper was accepted to NeurIPS (2023).
- One paper was accepted to ICLR (2023).
- One paper was accepted to ICASSP (2023).
- One paper was accepted to VLSI-SoC (2022), and won best paper nomination!!!
Preprint
Ling-Hao Chen*, Shunlin Lu*, Yukai Shi, Ailing Zeng, Ruimao Zhang, Lei Zhang,
This is the FIRST LLM-based (billion level) motion understanding model.
MotionLLM: Understanding Human Behaviors from Human Motions and Videos.
Ling-Hao Chen*,
Shunlin Lu*,
Ailing Zeng,
Hao Zhang,
Benyou Wang,
Ruimao Zhang,
Lei Zhang,
Arxiv Preprint 2024 [Project Page] | [Preprint] | [Code] | [Demo]
Publications
Play-and-plugin module for high-quality text-to-3D generation
HumanTOMATO: Text-aligned Whole-body Motion Generation
Shunlin Lu*,
Ling-Hao Chen*,
Ailing Zeng,
Jing Lin,
Ruimao Zhang,
Lei Zhang,
Heung-Yeung Shum.
ICML 2024 [Project Page] | [Preprint] | [Code] | [Video]
Motion-x: A large-scale 3d expressive whole-body human motion dataset
Jing Lin*, Ailing Zeng*, Shunlin Lu*, Yuanhao Cai, Ruimao Zhang, Haoqian Wang, Lei Zhang
NeurIPS 2023 [WebPage] [Paper] [Code] [Video 1] [Video 2]
Learning to linearize deep neural networks for secure and efficient private inference
Souvik Kundu*,
Shunlin Lu*,
Yuke Zhang,
Jacqueline T.Liu,
Peter A.Beerel
International Conference on Learning Representations (ICLR 2023)
[Paper]
Sparse mixture once-for-all adversarial training for efficient in-situ trade-off between accuracy and robustness of dnns
Souvik Kundu,
Sairam Sundaresan,
Sharath Nittur Sridhar,
Shunlin Lu,
Han Tang,
Peter A.Beerel
ICASSP 2023 [Paper]
P2M-DeTrack: Processing-in-Pixel-in-Memory for Energy-efficient and Real-Time Multi-Object Detection and Tracking
Gourav Datta,
Souvik Kundu,
Zihan Yin,
Joe Mathai,
Zeyu Liu,
Zixu Wang,
Shunlin Lu,
Ravi Lakkireddy,
Andrew Schmidt,
Wael Abd-Almageed,
Ajey Jacob,
Akhilesh Jaiswal,
Peter A.Beerel
IEEE VLSI-SoC 2022 [Paper]
(Best Paper Nomination)
Experience
| Shanghai Artificial Intelligence Labortary | Research intern | 2024.06 – now |
| International Digital Economy Academy (IDEA) | Research intern | 2023.01 – 2024.06 |
Awards & Honors
- Viterbi Honor Graduate Student in USC
- The First scholarship and titled the Superior Student in Wuhan University of Technology(three times)
Thanks to Weiyu Li and HTML5 UP for the design of this webpage.