In this paper, we propose a triangle-based view interpolation algorithm which can correctly resolve the visibility problem without depth-buffering. The algorithm is especially useful when depth information is not available, such as in the case of real-world photographs. By subdividing the reference image into variable-sized triangles, view interpolation can be done efficiently using existing gr...

In the past decade, multi-view clustering has received a lot of attention due to popularity data. However, not all samples can be observed from every view some unavoidable factors, resulting in incomplete (IMC) problem. Up until now, most efforts for IMC problem have been made on learning consensus representations or graphs, while many missing views are ignored, making it impossible capture inf...

A novel method for comparing non-aligned graphs of various sizes is proposed, based on the Wasserstein distance between graph signal distributions induced by respective Laplacian matrices. Specifically, a new formulation one-to-many alignment problem casted, which aims at matching node in smaller with one or more nodes larger graph. By incorporating optimal transport into our comparison framewo...

In this paper, we study the problem of MOOC quality evaluation that is essential for improving course materials, promoting students' learning efficiency, and benefiting user services. While achieving promising performances, current works still suffer from complicated interactions relationships entities in platforms. To tackle challenges, formulate as a representation task based, develop an Info...

In practical applications, multi-view data depicting objects from assorted perspectives can facilitate the accuracy increase of learning algorithms. However, given data, there is limited work for discriminative node relationships and graph information simultaneously via convolutional network that has drawn attention considerable researchers in recent years. Most existing methods only consider w...