Causal Intervention for Sparse-View Gait Recognition
Author:
Affiliation:
1. University of Science and Technology of China, Hefei, China
2. Beijing Normal University & WATRIX.AI, Beijing, China
3. Institute of Automation, Chinese Academy of Sciences, Beijing, China
4. WATRIX.AI, Beijing, China
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3581783.3612124
Reference39 articles.
1. Gunawan Ariyanto and Mark S. Nixon . 2011. Model-based 3D gait biometrics . In 2011 International Joint Conference on Biometrics (IJCB). 1--7. Gunawan Ariyanto and Mark S. Nixon. 2011. Model-based 3D gait biometrics. In 2011 International Joint Conference on Biometrics (IJCB). 1--7.
2. Random projection in dimensionality reduction
3. View-independent human motion classification using image-based reconstruction
4. Silhouette-Based View-Embeddings for Gait Recognition Under Multiple Views
5. Krzysztof Chalupka , Pietro Perona , and Frederick Eberhardt . 2015. Visual Causal Feature Learning (UAI'15) . AUAI Press , Arlington, Virginia, USA , 181--190. Krzysztof Chalupka, Pietro Perona, and Frederick Eberhardt. 2015. Visual Causal Feature Learning (UAI'15). AUAI Press, Arlington, Virginia, USA, 181--190.
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