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Subject Mode Variational LSTM (by Wissam) is accepted in AAAI 2019
Date 2018-11-01
Mode variational LSTM robust to unseen modes of variation has been accepted in AAAI 2019 (acceptance rate: 16.2 %).

The paper title is " Mode Variational LSTM Robust to Unseen Modes of Variation: Application to Facial Expression Recognition". The spatio-temporal feature encoding in deep learning is essential for encoding the dynamics in video sequences. Recurrent neural networks, particularly long short-term memory (LSTM) units, have been popular as an efficient tool for encoding spatio-temporal features for moving objects. This paper presents the mode variational LSTM to encode spatiotemporal features robust to unseen modes of variation. The proposed mode variational LSTM has been verified to be useful for real-world spatio-temporal recognition.
This paper has been written by Wissam J. Baddar and Yong Man Ro.