Multimodal video classification with stacked contractive autoencoders
By Yanan Liu, Xiaoqing Feng, Zhiguang Zhou. 2016
100 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Signal Processing
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Francisco Herrera
- Salvador Garcia
- Wenzhong Guo
- Jianwen Wang
- Shiping Wang
- Dhanesh Ramachandram
- Graham W. Taylor
- M. J. Jesús
In Signal Processing
- Wenzhong Guo
- Graham W. Taylor
- M. J. Jesús
- Francisco Herrera
- Jianwen Wang
- Dhanesh Ramachandram
- Francisco Charte
- David Charte
Citations in the corpus
- A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines (2018, background): “In [114] the authors propose the MSCAE (Multimodal Stacked Contractive Autoencoder), an application-”
- Deep Multimodal Representation Learning: A Survey (2019, background): “For example, by the utilization of fused features from multimodalities, improved performance can be achieved in cross-media analysis tasks, such as video classification [6], event detection [7], [8], and sentiment analysis [9], [10].”
- Deep Multimodal Learning: A Survey on Recent Advances and Trends (2017, background): “Other related hybrid architectures include those of Sachan et al. [54] and Liu et al. [55].”