One-shot Face Reenactment with Dense Correspondence Estimation

One-shot face reenactment is a challenging task due to the identity mismatch between source and driving faces.Most existing methods fail to completely eliminate the interference of driving subjects’identity information,which may lead to face shape distortion and undermine the realism of reenactment results.To solve this problem,in this paper,we propose using a 3D morphable model(3DMM)for explicit facial semantic decomposition and identity disentanglement.Instead of using 3D coefficients alone for reenactment control,we take advantage of the generative ability of 3DMM to render textured face proxies.These proxies contain abundant yet compact geometric and semantic information of human faces,which enables us to compute the face motion field between source and driving images by estimating the dense correspondence.In this way,we can approximate reenactment results by warping source images according to the motion field,and a generative adversarial network(GAN)is adopted to further improve the visual quality of warping results.Extensive experiments on various datasets demonstrate the advantages of the proposed method over existing state-of-the-art benchmarks in both identity preservation and reenactment fulfillment.

A Proposed Exercise to Reinforce Abstract Thinking for Upper-Division Computer and Electrical Engineering Students: Modeling a High-Speed Inverter Using Cognitive Representations and Abstract Algebra

In mathematics, physics, and engineering, abstract concepts are an indispensable foundation for the study and comprehension of concrete models. As concepts within these fields become increasingly detached from physical entities and more associated with mental events, thinking shifts from analytical to conceptual-abstract. Fundamental topics taken from the abstract algebra (aka: modern algebra) are unquestionably abstract. Historically, fundamental concepts taught from the abstract algebra are detached from physical reality with one exception: Boolean operations. Even so, many abstract algebra texts present Boolean operations from a purely mathematical operator perspective that is detached from physical entities. Some texts on the abstract algebra introduce logic gate circuits, but treat them as perceptual symbols. For majors of pure or applied mathematics, detachments from physical entities is not relevant. For students of Computer and Electrical Engineering (CpE/EE), mental associations of Boolean operations are essential, and one might argue that studying pure Boolean axioms are unnecessary mental abstractions. But by its nature, the CpE/EE field tends to be more mentally abstract than the other engineering disciplines. The depth of the mathematical abstractions that we teach to upper-division CpE/EE majors is certainly up for questioning.

Game Selection Method for Game-Based History Learning

Games that are used in research on game-based learning and serious games that are used for education are usually exclusive,making it difficult for teachers to attempt new methods in education.According to the data published in 2009 by the European Schoolnet(EUN),a network of European Ministries of Education,most of the problems that teachers face when using games in class are related to game selection.Based on the aforementioned data,this study presents a set of criteria for selecting games in order to solve the inconvenience experienced by teachers.The games,which are used as teaching materials for game-based learning,have been replaced with commercial games that are easily purchased,rather than serious games that are difficult to obtain the licensing.Based on the criteria,two games were selected in this study and the classes were conducted at the educational site.Compared to the group trained with textbooks,it has been confirmed that the effect of game-based learning was sufficient.In addition,five out of ten problems that teachers face were resolved.