Cross-View Action Recognition over Heterogeneous Feature Spaces

By Xinxiao Wu, Han Wang, Cuiwei Liu, Yunde Jia. 2013

70 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Biomedical Engineering, Computer Vision and Pattern Recognition

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Cuiling Lan
2. Wenjun Zeng
3. Nanning Zheng
4. Junliang Xing
5. Pengfei Zhang
6. Jianru Xue
7. G. Wang
8. Jun Liu

In Biomedical Engineering

1. Nanning Zheng
2. Pengfei Zhang
3. Jianru Xue
4. Cuiling Lan
5. Wenjun Zeng
6. Junliang Xing
7. Liang Wang
8. Jian Cheng

In Computer Vision and Pattern Recognition

1. Wenjun Zeng
2. Pengfei Zhang
3. Jianru Xue
4. Cuiling Lan
5. Nanning Zheng
6. Junliang Xing
7. Liang Wang
8. G. Wang

Citations in the corpus

• View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data (2017, background): “One category of approaches requires multiple view videos for training [15, 8, 41, 44, 25].”
• View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition (2018, background): “Some attempts have been made in previous works to overcome the view variation problem for robust action recognition [3], [8], [9], [14], [15], [19], [24], [26], [31], [36], [37], [39], [40], [50], [52], [53], [60].”
• Transfer Neural Trees for Heterogeneous Domain Adaptation (2016, unknown): “[20] proposed an algorithm of heterogeneous transfer discriminantanalysis of canonical correlations (HTDCC), which optimizes the canonical correlations of between the observed data.”