For a long time, the point cloud completion task has been regarded as pure generation task. After obtaining global shape code through encoder, complete is generated using priorly learnt by networks. However, such models are undesirably biased towards prior average objects and inherently limited to fit geometry details. In this letter, we propose Graph-Guided Deformation Network, which respectiv...

An outerplanar graph is a planar graph which can be embedded in the plane in such a way that all of vertices lie on the outer boundary. Many semi-structured data like the NCI dataset having about 250,000 chemical compounds can be expressed by outerplanar graphs. In this paper, we consider a data mining problem of extracting structural features from semi-structured data like the NCI dataset. For...

Let $G$ be a graph. Let $f:V(G)to{0,1,2, ldots, k-1}$ be a map where $k in mathbb{N}$ and $k>1$. For each edge $uv$, assign the label $left|f(u)-f(v)right|$. $f$ is called a $k$-total difference cordial labeling of $G$ if $left|t_{df}(i)-t_{df}(j)right|leq 1$, $i,j in {0,1,2, ldots, k-1}$ where $t_{df}(x)$ denotes the total number of vertices and the edges labeled with $x$.A graph with admits a...

Graph-based semi-supervised learning methods are based on some smoothness assumption about the data. As a discrete approximation of the data manifold, the graph plays a crucial role in the success of such graphbased methods. In most existing methods, graph construction makes use of a predefined weighting function without utilizing label information even when it is available. In this work, by in...