Nice to meet you, I'm Zenan Li

San Jose, CA, USA

If you have any questions, feel free to contact me by zenanlicareer@gmail.com
Check out my projects
My Background / About Me
I’m a Research and Development Engineer at Deepmotion since 2019. I obtained my M.S. Degree supervised by Prof. Mikhail Gofman at California State University, Fullerton in 2019. After that I was supervised by Prof. Libin Liu for 2 years at Deepmotion.
My research interests include Computer Vision, Computer Graphic, Human Pose Estimation, Motion Generation, Multimodal Models, MLLM, Video Understanding, Parametric Video Generation, Object Detection and Tracking, Synthetic Data Augmentation to overcome data shortage
Publications/Patents
Enhancing Narratives with SayMotion's text-to-3D animation and LLMs
Siggraph 2024 -- Real-Time Live!
Kevin He, Annette Lapham, and Zenan Li
Methods and systems for detecting 3d poses from 2d images and editing 3d poses
US Patent
Kaichuan He, Jakub Stepien, Zenan Li, Grzegorz Kabza, Marcin Hulist, Mikolaj Korcz
Measuring dynamic body movement
US Patent
Jeffery Broderick, Douglas Van Blaricom, Jerome Lisk, Zenan Li, Sukhad Anand
Multiple-Person 3D Human Mesh Recovery from Single 2D Picture
Thesis
Zenan Li
My Work / My Projects *Github Pages bandwidth is low, if you click on READ MORE and get an empty page, please wait until it fully loaded
Text-Video-to-Motion
Keywords: Causal Transformer, Mask Transformer, VQVAE, MultiModal Models
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MLLM guided Text-Motion data synthesis
Keywords: MLLM, MultiModal Models, Data Analysis, Data Preprocessing, Clustering
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Text-to-Motion Improvements Summary
Keywords: RAG, LLM, Cross Attention
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Object Detection & Multi-person tracking
Keywords: Segment Anything, SSD, Person Re-ID, Location Prediction, CLIP, FaceNet
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Human(Face+Fingers+Body) Pose Estimation
Keywords: Face, Fingers, Body Pose Estimation, Synthetic Data Augmentation, Diffusion model fine-tune, Discriminator, Motion Deblur, Background Segmentation, Animal
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Avatar Video Virtual Try-On
An interesting application I developed. Keywords: Avatar Video Generation(Editing)
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