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20182022
most citedQuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars

119 citations · 136 across the 5 of their papers we have counts for

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6 papers · 1 filter

cs.CV2022119 cited

QuestSim: Human Motion Tracking from Sparse Sensors with Simulated Avatars

Alexander Winkler, Jungdam Won, Yuting Ye

Real-time tracking of human body motion is crucial for interactive and immersive experiences in AR/VR. However, very limited sensor data about the body is available from standalone…

cs.CV20212 cited

Identity-Disentangled Neural Deformation Model for Dynamic Meshes

Binbin Xu, Lingni Ma, Yuting Ye +3

Neural shape models can represent complex 3D shapes with a compact latent space. When applied to dynamically deforming shapes such as the human hands, however, they would need to p…

cs.CV2020

Fully Convolutional Mesh Autoencoder using Efficient Spatially Varying Kernels

Yi Zhou, Chenglei Wu, Zimo Li +5

Learning latent representations of registered meshes is useful for many 3D tasks. Techniques have recently shifted to neural mesh autoencoders. Although they demonstrate higher pre…

cs.CV20192 cited

Disentangling Pose from Appearance in Monochrome Hand Images

Yikang Li, Chris Twigg, Yuting Ye +2

Hand pose estimation from the monocular 2D image is challenging due to the variation in lighting, appearance, and background. While some success has been achieved using deep neural…

cs.CV2018

Learning Warped Guidance for Blind Face Restoration

Xiaoming Li, Ming Liu, Yuting Ye +3

This paper studies the problem of blind face restoration from an unconstrained blurry, noisy, low-resolution, or compressed image (i.e., degraded observation). For better recovery…

cs.CV2018

Going Deeper in Spiking Neural Networks: VGG and Residual Architectures

Abhronil Sengupta, Yuting Ye, Robert Wang +2

Over the past few years, Spiking Neural Networks (SNNs) have become popular as a possible pathway to enable low-power event-driven neuromorphic hardware. However, their application…