Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: DAR-Net: Dynamic Aggregation Network for Semantic Scene Segmentation   Traditional grid/neighbor-based static pooling has become a constraint for
point cloud geometry analysis. In this paper, we propose DAR-Net, a novel
network architecture that focuses on dynamic feature aggregation. The central
idea of DAR-Net is generating a self-adaptive pooling skeleton that considers
both scene complexity and local geometry features. Providing variable
semi-local receptive fields and weights, the skeleton serves as a bridge that
connect local convolutional feature extractors and a global recurrent feature
integrator. Experimental results on indoor scene datasets show advantages of
the proposed approach compared to state-of-the-art architectures that adopt
static pooling methods.

3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
37
The categories of this paper are: supr-con
18
The categories of this paper are: econ
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
34
The categories of this paper are: chem-ph
11
The categories of this paper are: hep-lat
21
The categories of this paper are: adap-org
12
The categories of this paper are: nucl-th
19
The categories of this paper are: eess