Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Rethinking Temporal Object Detection from Robotic Perspectives   Video object detection (VID) has been vigorously studied for years but almost
all literature adopts a static accuracy-based evaluation, i.e., average
precision (AP). From a robotic perspective, the importance of recall continuity
and localization stability is equal to that of accuracy, but the AP is
insufficient to reflect detectors' performance across time. In this paper,
non-reference assessments are proposed for continuity and stability based on
object tracklets. These temporal evaluations can serve as supplements to static
AP. Further, we develop an online tracklet refinement for improving detectors'
temporal performance through short tracklet suppression, fragment filling, and
temporal location fusion.
  In addition, we propose a small-overlap suppression to extend VID methods to
single object tracking (SOT) task so that a flexible SOT-by-detection framework
is then formed.
  Extensive experiments are conducted on ImageNet VID dataset and real-world
robotic tasks, where the superiority of our proposed approaches are validated
and verified. Codes will be publicly available.

31
The categories of this paper are: ao-sci
37
The categories of this paper are: supr-con
9
The categories of this paper are: nlin
20
The categories of this paper are: acc-phys
5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
2
The categories of this paper are: math
29
The categories of this paper are: funct-an
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
0
The categories of this paper are: hep-ph
35
The categories of this paper are: mtrl-th