DyGait: Exploiting Dynamic Representations for High-performance Gait Recognition
Author:
Affiliation:
1. Beijing Jiaotong University
2. PhiGent Robotics
3. National University of Singapore
4. NetEase Fuxi AI Lab
5. University of Queensland
Funder
National Natural Science Foundation of China
Fundamental Research Funds for the Central Universities
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10376473/10376477/10376804.pdf?arnumber=10376804
Reference69 articles.
1. Gait recognition without subject cooperation
2. Lagrange Motion Analysis and View Embeddings for Improved Gait Recognition
3. Semantically-Guided Disentangled Representation for Robust Gait Recognition
4. Silhouette-Based View-Embeddings for Gait Recognition Under Multiple Views
5. GaitSet: Regarding Gait as a Set for Cross-View Gait Recognition
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