Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Panoptic SwiftNet: Pyramidal Fusion for Real-time Panoptic Segmentation   Dense panoptic prediction is a key ingredient in many existing applications
such as autonomous driving, automated warehouses or agri-robotics. However,
most of these applications leverage the recovered dense semantics as an input
to visual closed-loop control. Hence, practical deployments require real-time
inference over large input resolutions on embedded hardware. These requirements
call for computationally efficient approaches which deliver high accuracy with
limited computational resources. We propose to achieve this goal by trading-off
backbone capacity for multi-scale feature extraction. In comparison with
contemporaneous approaches to panoptic segmentation, the main novelties of our
method are scale-equivariant feature extraction and cross-scale upsampling
through pyramidal fusion. Our best model achieves 55.9% PQ on Cityscapes val at
60 FPS on full resolution 2MPx images and RTX3090 with FP16 Tensor RT
optimization.

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The categories of this paper are: chao-dyn
28
The categories of this paper are: alg-geom
24
The categories of this paper are: dg-ga
15
The categories of this paper are: nucl-ex
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
33
The categories of this paper are: plasm-ph
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
9
The categories of this paper are: nlin
19
The categories of this paper are: eess
2
The categories of this paper are: math
34
The categories of this paper are: chem-ph
17
The categories of this paper are: q-fin
31
The categories of this paper are: ao-sci