Search Results for author: Yuxuan Mu

Found 4 papers, 2 papers with code

Generative Human Motion Stylization in Latent Space

no code implementations24 Jan 2024 Chuan Guo, Yuxuan Mu, Xinxin Zuo, Peng Dai, Youliang Yan, Juwei Lu, Li Cheng

Building upon this, we present a novel generative model that produces diverse stylization results of a single motion (latent) code.

MoMask: Generative Masked Modeling of 3D Human Motions

1 code implementation29 Nov 2023 Chuan Guo, Yuxuan Mu, Muhammad Gohar Javed, Sen Wang, Li Cheng

For the base-layer motion tokens, a Masked Transformer is designated to predict randomly masked motion tokens conditioned on text input at training stage.

Human motion prediction Motion Forecasting +2

Event-based Human Pose Tracking by Spiking Spatiotemporal Transformer

1 code implementation16 Mar 2023 Shihao Zou, Yuxuan Mu, Xinxin Zuo, Sen Wang, Li Cheng

Motivated by the above mentioned issues, we present in this paper a dedicated end-to-end sparse deep learning approach for event-based pose tracking: 1) to our knowledge this is the first time that 3D human pose tracking is obtained from events only, thus eliminating the need of accessing to any frame-based images as part of input; 2) our approach is based entirely upon the framework of Spiking Neural Networks (SNNs), which consists of Spike-Element-Wise (SEW) ResNet and a novel Spiking Spatiotemporal Transformer; 3) a large-scale synthetic dataset is constructed that features a broad and diverse set of annotated 3D human motions, as well as longer hours of event stream data, named SynEventHPD.

3D Human Pose Estimation 3D Human Pose Tracking

Automatic Analysis System of Calcaneus Radiograph: Rotation-Invariant Landmark Detection for Calcaneal Angle Measurement, Fracture Identification and Fracture Region Segmentation

no code implementations10 Dec 2019 Jia Guo, Yuxuan Mu, Dong Xue, Huiqi Li, Junxian Chen, Huanxin Yan, Hailin Xu, Wei Wang

This study aims to develop an analysis system that can automatically locate four anatomic landmarks, measure BA and CAG for fracture assessment, identify fractured calcaneus, and segment fractured regions.

Multi-Task Learning Segmentation

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