Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Road Scene Graph: A Semantic Graph-Based Scene Representation Dataset
  for Intelligent Vehicles   Rich semantic information extraction plays a vital role on next-generation
intelligent vehicles. Currently there is great amount of research focusing on
fundamental applications such as 6D pose detection, road scene semantic
segmentation, etc. And this provides us a great opportunity to think about how
shall these data be organized and exploited.
  In this paper we propose road scene graph,a special scene-graph for
intelligent vehicles. Different to classical data representation, this graph
provides not only object proposals but also their pair-wise relationships. By
organizing them in a topological graph, these data are explainable,
fully-connected, and could be easily processed by GCNs (Graph Convolutional
Networks). Here we apply scene graph on roads using our Road Scene Graph
dataset, including the basic graph prediction model. This work also includes
experimental evaluations using the proposed model.

23
The categories of this paper are: solv-int
16
The categories of this paper are: stat
19
The categories of this paper are: eess
8
The categories of this paper are: hep-ex
4
The categories of this paper are: cond-mat
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
20
The categories of this paper are: acc-phys
10
The categories of this paper are: q-bio
37
The categories of this paper are: supr-con
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph