Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Privacy-preserving Object Detection   Privacy considerations and bias in datasets are quickly becoming
high-priority issues that the computer vision community needs to face. So far,
little attention has been given to practical solutions that do not involve
collection of new datasets. In this work, we show that for object detection on
COCO, both anonymizing the dataset by blurring faces, as well as swapping faces
in a balanced manner along the gender and skin tone dimension, can retain
object detection performances while preserving privacy and partially balancing
bias.

18
The categories of this paper are: econ
20
The categories of this paper are: acc-phys
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
13
The categories of this paper are: quant-ph
25
The categories of this paper are: patt-sol
7
The categories of this paper are: hep-th
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
3
The categories of this paper are: physics
30
The categories of this paper are: q-alg
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
37
The categories of this paper are: supr-con
16
The categories of this paper are: stat
29
The categories of this paper are: funct-an