Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Continuous Conditional Random Field Convolution for Point Cloud
  Segmentation   Point cloud segmentation is the foundation of 3D environmental perception for
modern intelligent systems. To solve this problem and image segmentation,
conditional random fields (CRFs) are usually formulated as discrete models in
label space to encourage label consistency, which is actually a kind of
postprocessing. In this paper, we reconsider the CRF in feature space for point
cloud segmentation because it can capture the structure of features well to
improve the representation ability of features rather than simply smoothing.
Therefore, we first model the point cloud features with a continuous quadratic
energy model and formulate its solution process as a message-passing graph
convolution, by which it can be easily integrated into a deep network. We
theoretically demonstrate that the message passing in the graph convolution is
equivalent to the mean-field approximation of a continuous CRF model.
Furthermore, we build an encoder-decoder network based on the proposed
continuous CRF graph convolution (CRFConv), in which the CRFConv embedded in
the decoding layers can restore the details of high-level features that were
lost in the encoding stage to enhance the location ability of the network,
thereby benefiting segmentation. Analogous to the CRFConv, we show that the
classical discrete CRF can also work collaboratively with the proposed network
via another graph convolution to further improve the segmentation results.
Experiments on various point cloud benchmarks demonstrate the effectiveness and
robustness of the proposed method. Compared with the state-of-the-art methods,
the proposed method can also achieve competitive segmentation performance.

34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
13
The categories of this paper are: quant-ph
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
5
The categories of this paper are: gr-qc
2
The categories of this paper are: math
10
The categories of this paper are: q-bio
30
The categories of this paper are: q-alg
9
The categories of this paper are: nlin
37
The categories of this paper are: supr-con
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph