Abstract Facial expressions are an important part of human emotional signals and their recognition has become topic research in the field pattern recognition. Deep learning based methods have achieved great success facial expressions. However, with evolution convolution neural networks increased network depth, these suffer from problems such as degraded performance loss feature information. To ...

Facial micro-expression is a superposition of features and identity information subject. For the problem interference in recognition, this study proposes new method for facial recognition by de-identity information, called two-stream difference network (TSDN). First, encoder-decoder trained convolutional neural network, where input stream image, image. The image apex onset sequence. are recorde...

Micro-Expression Recognition (MER) is challenging because the Micro-Expressions' (ME) motion too weak to distinguish. This hurdle can be tackled by enhancing intensity for a more accurate acquisition of movements. However, existing magnification strategies tend use features facial images that include not only clues as features, leading representation deficient credibility. In addition, variatio...