Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: NViSII: A Scriptable Tool for Photorealistic Image Generation   We present a Python-based renderer built on NVIDIA's OptiX ray tracing engine
and the OptiX AI denoiser, designed to generate high-quality synthetic images
for research in computer vision and deep learning. Our tool enables the
description and manipulation of complex dynamic 3D scenes containing object
meshes, materials, textures, lighting, volumetric data (e.g., smoke), and
backgrounds. Metadata, such as 2D/3D bounding boxes, segmentation masks, depth
maps, normal maps, material properties, and optical flow vectors, can also be
generated. In this work, we discuss design goals, architecture, and
performance. We demonstrate the use of data generated by path tracing for
training an object detector and pose estimator, showing improved performance in
sim-to-real transfer in situations that are difficult for traditional
raster-based renderers. We offer this tool as an easy-to-use, performant,
high-quality renderer for advancing research in synthetic data generation and
deep learning.

9
The categories of this paper are: nlin
31
The categories of this paper are: ao-sci
34
The categories of this paper are: chem-ph
16
The categories of this paper are: stat
24
The categories of this paper are: dg-ga
17
The categories of this paper are: q-fin
5
The categories of this paper are: gr-qc
21
The categories of this paper are: adap-org
37
The categories of this paper are: supr-con
3
The categories of this paper are: physics
36
The categories of this paper are: cmp-lg
7
The categories of this paper are: hep-th
2
The categories of this paper are: math
19
The categories of this paper are: eess
14
The categories of this paper are: math-ph
8
The categories of this paper are: hep-ex