Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: SynthCam3D: Semantic Understanding With Synthetic Indoor Scenes   We are interested in automatic scene understanding from geometric cues. To
this end, we aim to bring semantic segmentation in the loop of real-time
reconstruction. Our semantic segmentation is built on a deep autoencoder stack
trained exclusively on synthetic depth data generated from our novel 3D scene
library, SynthCam3D. Importantly, our network is able to segment real world
scenes without any noise modelling. We present encouraging preliminary results.

31
The categories of this paper are: ao-sci
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
35
The categories of this paper are: mtrl-th
10
The categories of this paper are: q-bio
24
The categories of this paper are: dg-ga
13
The categories of this paper are: quant-ph
16
The categories of this paper are: stat
0
The categories of this paper are: hep-ph
14
The categories of this paper are: math-ph
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con