Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: VLP: A Survey on Vision-Language Pre-training   In the past few years, the emergence of pre-training models has brought
uni-modal fields such as computer vision (CV) and natural language processing
(NLP) to a new era. Substantial works have shown they are beneficial for
downstream uni-modal tasks and avoid training a new model from scratch. So can
such pre-trained models be applied to multi-modal tasks? Researchers have
explored this problem and made significant progress. This paper surveys recent
advances and new frontiers in vision-language pre-training (VLP), including
image-text and video-text pre-training. To give readers a better overall grasp
of VLP, we first review its recent advances from five aspects: feature
extraction, model architecture, pre-training objectives, pre-training datasets,
and downstream tasks. Then, we summarize the specific VLP models in detail.
Finally, we discuss the new frontiers in VLP. To the best of our knowledge,
this is the first survey on VLP. We hope that this survey can shed light on
future research in the VLP field.

16
The categories of this paper are: stat
9
The categories of this paper are: nlin
23
The categories of this paper are: solv-int
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
4
The categories of this paper are: cond-mat
31
The categories of this paper are: ao-sci
26
The categories of this paper are: bayes-an
0
The categories of this paper are: hep-ph
20
The categories of this paper are: acc-phys
2
The categories of this paper are: math
30
The categories of this paper are: q-alg
33
The categories of this paper are: plasm-ph
34
The categories of this paper are: chem-ph
14
The categories of this paper are: math-ph