Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deflating Dataset Bias Using Synthetic Data Augmentation   Deep Learning has seen an unprecedented increase in vision applications since
the publication of large-scale object recognition datasets and introduction of
scalable compute hardware. State-of-the-art methods for most vision tasks for
Autonomous Vehicles (AVs) rely on supervised learning and often fail to
generalize to domain shifts and/or outliers. Dataset diversity is thus key to
successful real-world deployment. No matter how big the size of the dataset,
capturing long tails of the distribution pertaining to task-specific
environmental factors is impractical. The goal of this paper is to investigate
the use of targeted synthetic data augmentation - combining the benefits of
gaming engine simulations and sim2real style transfer techniques - for filling
gaps in real datasets for vision tasks. Empirical studies on three different
computer vision tasks of practical use to AVs - parking slot detection, lane
detection and monocular depth estimation - consistently show that having
synthetic data in the training mix provides a significant boost in
cross-dataset generalization performance as compared to training on real data
only, for the same size of the training set.

8
The categories of this paper are: hep-ex
0
The categories of this paper are: hep-ph
36
The categories of this paper are: cmp-lg
22
The categories of this paper are: chao-dyn
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
14
The categories of this paper are: math-ph
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
24
The categories of this paper are: dg-ga
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con