Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: PETR: Position Embedding Transformation for Multi-View 3D Object
  Detection   In this paper, we develop position embedding transformation (PETR) for
multi-view 3D object detection. PETR encodes the position information of 3D
coordinates into image features, producing the 3D position-aware features.
Object query can perceive the 3D position-aware features and perform end-to-end
object detection. PETR achieves state-of-the-art performance (50.4% NDS and
44.1% mAP) on standard nuScenes dataset and ranks 1st place on the benchmark.
It can serve as a simple yet strong baseline for future research.

10
The categories of this paper are: q-bio
0
The categories of this paper are: hep-ph
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
26
The categories of this paper are: bayes-an
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
3
The categories of this paper are: physics
20
The categories of this paper are: acc-phys
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
8
The categories of this paper are: hep-ex
2
The categories of this paper are: math
32
The categories of this paper are: atom-ph