Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Associating Objects with Scalable Transformers for Video Object
  Segmentation   This paper investigates how to realize better and more efficient embedding
learning to tackle the semi-supervised video object segmentation under
challenging multi-object scenarios. The state-of-the-art methods learn to
decode features with a single positive object and thus have to match and
segment each target separately under multi-object scenarios, consuming multiple
times computation resources. To solve the problem, we propose an Associating
Objects with Transformers (AOT) approach to match and decode multiple objects
jointly and collaboratively. In detail, AOT employs an identification mechanism
to associate multiple targets into the same high-dimensional embedding space.
Thus, we can simultaneously process multiple objects' matching and segmentation
decoding as efficiently as processing a single object. To sufficiently model
multi-object association, a Long Short-Term Transformer (LSTT) is devised to
construct hierarchical matching and propagation. Based on AOT, we further
propose a more flexible and robust framework, Associating Objects with Scalable
Transformers (AOST), in which a scalable version of LSTT is designed to enable
run-time adaptation of accuracy-efficiency trade-offs. Besides, AOST introduces
a better layer-wise manner to couple identification and vision embeddings. We
conduct extensive experiments on multi-object and single-object benchmarks to
examine AOT series frameworks. Compared to the state-of-the-art competitors,
our methods can maintain times of run-time efficiency with superior
performance. Notably, we achieve new state-of-the-art performance on three
popular benchmarks, i.e., YouTube-VOS (86.5%), DAVIS 2017 Val/Test
(87.0%/84.7%), and DAVIS 2016 (93.0%). Project page:
https://github.com/z-x-yang/AOT.

18
The categories of this paper are: econ
3
The categories of this paper are: physics
17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
6
The categories of this paper are: astro-ph
34
The categories of this paper are: chem-ph
21
The categories of this paper are: adap-org
33
The categories of this paper are: plasm-ph
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
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The categories of this paper are: comp-gas
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The categories of this paper are: nucl-th
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The categories of this paper are: acc-phys
9
The categories of this paper are: nlin