Camera-Selecting Device-Edge Co-Inference for Real-Time Multi-Camera 3D Pose Estimation-Reference-Cited by-同舟云学术

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Camera-Selecting Device-Edge Co-Inference for Real-Time Multi-Camera 3D Pose Estimation

Published:2023-10-10 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
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Author:

Du Zhuohang¹,Huang Xumin¹,Wu Yuan¹,Tan Pengcheng¹,Li Peichun¹,Qian Liping²,Zhou Haibo³

Affiliation:

1. University of Macau,State Key Laboratory of Internet of Things for Smart City,Macau,China

2. Zhejiang University of Technology,College of Information Engineering,Hangzhou,China

3. Nanjing University,School of Electronic Science and Engineering,Nanjing,China

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10333258/10333344/10333552.pdf?arnumber=10333552

Reference17 articles.

1. Deep High-Resolution Representation Learning for Human Pose Estimation

2. VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild

3. Predicting Task-Driven Attention via Integrating Bottom-Up Stimulus and Top-Down Guidance

4. Fast and Robust Multi-Person 3D Pose Estimation and Tracking from Multiple Views

5. Non-Orthogonal Multiple Access Assisted Federated Learning via Wireless Power Transfer: A Cost-Efficient Approach

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