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Paper

A Survey on Vision Transformer

by Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, D. Tao 2012.12556

Free2AITools Nexus Index

63.9

S: Semantic 50

Query-time baseline · scored live at search

A: Authority 94

P: Popularity 76

R: Recency 100

Q: Quality 65

Tech Context

Vital Performance —

Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks to its strong representation capabilities, researchers are looking at ways to apply transformer to computer vision tasks. In a variety of visual benchmarks, transformer-based models perform similar to or better than other types of networks such as convolutional and recurrent neural networks. Given its high performance and less need for v...

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Semantic Scholar 3.2K Citations

Paper Information Summary
Entity Passport
Registry ID	2012.12556
License	ArXiv
Provider	semantic_scholar

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Cite this paper

Academic & Research Attribution

BibTeX

@misc{arxiv_2012_12556,
  author = {Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, D. Tao},
  title = {A Survey on Vision Transformer Paper},
  year = {2026},
  howpublished = {\url{https://arxiv.org/abs/2012.12556}},
  note = {Accessed via Free2AITools.}
}

APA Style

Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, D. Tao. (2026). A Survey on Vision Transformer [Paper]. Free2AITools. https://arxiv.org/abs/2012.12556

🔬Technical Deep Dive

Full Specifications [+]

⚖️ Free2AITools Nexus Index V2.0

Methodology How FNI works

Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 94

Popularity (P) 76

Recency (R) 100

Quality (Q) 65

💬 Index Insight

FNI V2.0 for A Survey on Vision Transformer: Authority (A:94), Popularity (P:76), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

Data Sources / Provenance

HuggingFace API GitHub Metadata Arxiv Citation DB Methodology

Open data Updated: Live data

📝 Executive Summary

"Transformer, first applied to the field of natural language processing, is a type of deep neural network mainly based on the self-attention mechanism. Thanks to its strong representation capabilities, researchers are looking at ways to apply transformer to computer vision tasks. In a variety of visual benchmarks, transformer-based models perform similar to or better than other types of networks such as convolutional and recurrent neural networks. Given its high performance and less need for v..."

❝ Cite Node

@article{Han2026A,
  title={A Survey on Vision Transformer},
  author={Kai Han and Yunhe Wang and Hanting Chen and Xinghao Chen and Jianyuan Guo and Zhenhua Liu and Yehui Tang and An Xiao and Chunjing Xu and Yixing Xu and Zhaohui Yang and Yiman Zhang and D. Tao},
  journal={arXiv preprint arXiv:2012.12556},
  year={2026}
}

👥 Collaborating Minds

Kai Han Yunhe Wang Hanting Chen Xinghao Chen Jianyuan Guo Zhenhua Liu Yehui Tang An Xiao Chunjing Xu Yixing Xu Zhaohui Yang Yiman Zhang D. Tao

🔗 Full Paper

Free2AITools indexes the abstract and factual metadata for this paper. Read the complete, authoritative paper on the official source.

Read the full paper on arXiv

📊 Research Signals

📈3,168CitationsSemantic Scholar

🏛️94AuthorityFNI pillar

⏱️100RecencyFNI pillar

✅65QualityFNI pillar

🗂️vision multimediaField

🏷️ Research Topics

vision modelstransformer architectureattention mechanism

📦Data Source: semantic_scholar

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Source summary: Based on semantic_scholar metadata. Not a recommendation.

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🛡️ Paper Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: 2012.12556
slug: 2012.12556
source: semantic_scholar
author: Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, Zhaohui Yang, Yiman Zhang, D. Tao
license: ArXiv
tags: paper, research, academic

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag

📊 Engagement & Metrics

downloads: 0
stars: 0
forks: 0
citations: 3,168

Data indexed from public sources. Updated daily.