Yuting Ye
About Yuting Ye
- Affiliations
- Georgia Institute of Technology (Georgia Tech), Research Scientist
- University of Southern California (USC)
- Industrial Light & Magic
- Meta
- Bio
SIGGRAPH Asia 2020
Yuting Ye is a research scientist at Facebook Reality Labs. She works on human tracking and user interaction techniques to shape artificial (virtual, augmented, or mixed) realities as the future computing platform. Her recent research focuses on accurate skeletal hand tracking for virtual reality applications. She is especially interested in combining prior knowledge of human motion into modern deep learning formulation. She holds a PhD in computer science from Georgia Institute of Technology on the simulation and control of character animation.
SIGGRAPH 2020
Yuting Ye is a research scientist at Facebook Reality Labs. She works on human tracking and user interaction techniques to shape artificial (virtual, augmented, or mixed) realities as the future computing platform. Her recent research focuses on accurate skeletal hand tracking for virtual reality applications. She is especially interested in combining prior knowledge of human motion in deep learning problems. She holds a PhD in computer science from Georgia Institute of Technology on the simulation and control of virtual characters.
SIGGRAPH Conference Organizing Committee Positions
- Committee Member
- SIGGRAPH Asia 2018: Courses
- SIGGRAPH Asia 2024: Courses
- SIGGRAPH Asia 2021: Technical Papers
- SIGGRAPH Asia 2023: Technical Papers
- Jury Member
- SIGGRAPH 2019: Technical Papers
Conference Contributions
- Presentations
-
Presenter(s):Entry #: 73
Presenter(s):Entry #: 08 - Sessions Moderated
- “RSMT: Real-time Stylized Motion Transition for Characters” by Tang, Wu, Wang, Hu, Gong, et al. …
- “Learning Physically Simulated Tennis Skills from Broadcast Videos” by Zhang, Makoviychuk, Yuan, Guo, Fidler, et al. …
- “Example-based Motion Synthesis via Generative Motion Matching” by Li, Chen, Li, Sorkine-Hornung and Chen
- “DOC: Differentiable Optimal Control for Retargeting Motions onto Legged Robots” by Grandia, Knoop, Schumacher, Hutter and Bächer
- “Composite Motion Learning with Task Control” by Xu, Shang, Zordan and Karamouzas
- “CALM: Conditional Adversarial Latent Models for Directable Virtual Characters” by Tessler, Guo, Mannor, Chechik and Peng
Other Information
- Roles
- Course Presenter
- Courses Organizing Committee Member
- Talk (Sketch) Presenter
- Technical Paper Moderator
- Technical Paper Presenter
- Technical Papers Jury Member
- Technical Papers Organizing Committee Member
- Submit a Story
- If you would like to submit a story about this person (please keep it funny, informative and true), please contact us: historyarchives@siggraph.org
If you find errors or omissions on your profile page, please contact us: historyarchives@siggraph.org
Did you know you can send us a photo of yourself and a bio and we will post it? Make sure the photo is at least 1000 x 1000 and send it to the email above along with the bio and we will add it to your page.
