Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: BlendTorch: A Real-Time, Adaptive Domain Randomization Library   Solving complex computer vision tasks by deep learning techniques relies on
large amounts of (supervised) image data, typically unavailable in industrial
environments. The lack of training data starts to impede the successful
transfer of state-of-the-art methods in computer vision to industrial
applications. We introduce BlendTorch, an adaptive Domain Randomization (DR)
library, to help creating infinite streams of synthetic training data.
BlendTorch generates data by massively randomizing low-fidelity simulations and
takes care of distributing artificial training data for model learning in
real-time. We show that models trained with BlendTorch repeatedly perform
better in an industrial object detection task than those trained on real or
photo-realistic datasets.

12
The categories of this paper are: nucl-th
6
The categories of this paper are: astro-ph
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
28
The categories of this paper are: alg-geom
16
The categories of this paper are: stat
27
The categories of this paper are: comp-gas
0
The categories of this paper are: hep-ph
23
The categories of this paper are: solv-int
3
The categories of this paper are: physics
33
The categories of this paper are: plasm-ph
10
The categories of this paper are: q-bio
31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol