Facial Motion Prior Networks for Facial Expression Recognition

Deep learning based facial expression recognition (FER) has received a lot of attention in the past few years. Most of the existing deep learning based FER methods do not consider domain knowledge well, which thereby fail to extract representative features. In this work, we propose a novel FER framework, named Facial Motion Prior Networks (FMPN). Particularly, we introduce an addition branch to generate a facial mask so as to focus on facial muscle moving regions. To guide the facial mask learning, we propose to incorporate prior domain knowledge by using the average differences between neutral faces and the corresponding expressive faces as the training guidance. Extensive experiments on three facial expression benchmark datasets demonstrate the effectiveness of the proposed method, compared with the state-of-the-art approaches.Comment: VCIP 2019, Oral. Code is available at https://github.com/donydchen/FMPN-FE

Truthful resource management in wireless ad hoc networks

In wireless mobile ad hoc networks (MANETs), cooperation cannot be an im- plicit assumption anymore. Each profit-oriented network node has the intention to be selfish due to limited resource possession. In this dissertation, we investigate the truthful resource management that induces network nodes to reveal true information and stimulate cooperation. We propose the Transmission Power Recursive Auction Mechanism routing pro- tocol (TEAM) and the Truthful Topology Control mechanism (TRUECON) to cope with the selfish intention and achieve resource effciency in a non-cooperative envi- ronment. We prove both are strategy-proof and have some theoretic bounds on the performance. Compared with the existing routing protocols and topology control al- gorithms, TEAM and TRUECON are more effcient when dealing with the selfishness in MANETs. We conduct a study on anonymity enhancement in MANETs by reducing trans- mission power of network nodes. A routing protocol - Whisper is presented. Simu- lation results show that it has desirable properties in terms of anonymity and power effciency