MixSynthFormer: A Transformer Encoder-like Structure with Mixed Synthetic Self-attention for Efficient Human Pose Estimation-Reference-Cited by-同舟云学术

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MixSynthFormer: A Transformer Encoder-like Structure with Mixed Synthetic Self-attention for Efficient Human Pose Estimation

Published:2023-10-01 Issue: Volume:34 Page:14838-14847
ISSN:
Container-title:2023 IEEE/CVF International Conference on Computer Vision (ICCV)
language:
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Author:

Sun Yuran¹,Dougherty Alan William¹,Zhang Zhuoying¹,Choi Yi King¹,Wu Chuan¹

Affiliation:

1. The University of Hong Kong

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10376473/10376477/10376791.pdf?arnumber=10376791

Reference42 articles.

1. A Spatio-temporal Transformer for 3D Human Motion Prediction

2. Learning Progressive Joint Propagation for Human Motion Prediction

3. Realtime Multi-person 2D Pose Estimation Using Part Affinity Fields

4. MobileHumanPose: Toward real-time 3D human pose estimation in mobile devices

5. A review of 3D human pose estimation algorithms for markerless motion capture

Cited by 4 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Enhancing human pose estimation in sports training: Integrating spatiotemporal transformer for improved accuracy and real-time performance;Alexandria Engineering Journal;2024-12

2. Deep learning for 3D human pose estimation and mesh recovery: A survey;Neurocomputing;2024-09

3. Transformer with difference convolutional network for lightweight universal boundary detection;PLOS ONE;2024-04-16

4. MTAN: Multi-degree Tail-aware Attention Network for human motion prediction;Internet of Things;2024-04

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