TuSimple/tusimple-benchmark: papers linking to it

GitHub · 594 stars · 186 forks · Jupyter Notebook · license Apache-2.0 · created 2017 · github.com/TuSimple/tusimple-benchmark

← Code and data repositories cited in research papers

Research papers in the 480 tracked journals that link to TuSimple/tusimple-benchmark (https://github.com/TuSimple/tusimple-benchmark), read from their Crossref records: by year, category and journal, the family tree of papers building on one another, and the linked repositories derived from it or that it derives from.

Key findings#

9 papers in the tracked journals link to the GitHub repository TuSimple/tusimple-benchmark in their Crossref records, the first in 2021; most of them (3) in 2025.
By category: AI (9); the journals with the most are Pattern Recognition (3), Neural Computing and Applications (2) and Expert Systems with Applications (1).
2 of the papers build on one another: a later paper cites an earlier one that also links TuSimple/tusimple-benchmark.

By year#

20212026

Papers linking to TuSimple/tusimple-benchmark by publication year
Year	Papers
2021	1
2022	1
2023	3
2025	3
2026	1

Journals#

Journals whose papers link to TuSimple/tusimple-benchmark most
Journal	Papers
Pattern Recognition	3
Neural Computing and Applications	2
Expert Systems with Applications	1
Applied Intelligence	1
International Journal of Computer Vision	1

Family tree#

Each paper sits under the earlier paper it builds on; papers that cite no other paper here start a branch of their own.

Real-Time Lane Detection by Using Biologically Inspired Attention Mechanism to Learn Contextual Information Cognitive Computation, 2021
- AR-NET: lane detection model with feature balance concerns for autonomous driving Neural Computing and Applications, 2023 — cites the paper above

Papers linking to TuSimple/tusimple-benchmark, most cited first
Published	Title	Journal	Authors	Citations	Link
2022-09-21	Lane Detection with Versatile AtrousFormer and Local Semantic Guidance	Pattern Recognition	Jiaxing Yang, Lihe Zhang, Huchuan Lu	46	cites it
2023-07-08	LaneScanNET: A deep-learning approach for simultaneous detection of obstacle-lane states for autonomous driving systems	Expert Systems with Applications	P. Shunmuga Perumal, Yong Wang, M. Sujasree et al.	31	cites it
2021-09-01	Real-Time Lane Detection by Using Biologically Inspired Attention Mechanism to Learn Contextual Information	Cognitive Computation	Lu Zhang, Fengling Jiang, Bin Kong et al.	15	cites it
2025-03-24	LaneCorrect: Self-Supervised Lane Detection	International Journal of Computer Vision	Ming Nie, Xinyue Cai, Hang Xu et al.	7	cites it
2023-01-13	Non-residual unrestricted pruned ultra-faster line detection for edge devices	Pattern Recognition	Pengpeng Chen, Dongjingdian Liu, Shouwan Gao	5	cites it
2025-01-04	A comprehensive study of fisheye image compression and perception for autonomous driving	Neural Computing and Applications	Basem Barakat, Ibrahim Sobh, Chup-Chung Wong et al.	3	cites it
2023-12-08	AR-NET: lane detection model with feature balance concerns for autonomous driving	Neural Computing and Applications	Guoxiang Tong, Chuanye Zu	0	cites it
2025-12-27	Lane mark segmentation from sparse event image via lightweight large kernel network	Applied Intelligence	Mingyong Zhuang, Xinbo Chen, Yixiong Zhang et al.	0	cites it
2026-03-08	A lane detection model with knowledge guided anchor feature enhancement mechanism	Pattern Recognition	Zhixiong Nan, Wanying Xu, Zhe Yang et al.	0	cites it

How this is measured#

Links are read from each paper's Crossref record as its publisher deposited it: the URLs and repository DOIs in its reference list (the software and data it cites) and its supplementary links (“is-supplemented-by”: its own code or data). A paper that gives its code only in the text, a footnote or a data availability statement is not counted, and some publishers deposit reference lists without their URLs, so every count here is a lower bound. Repository details come from the GitHub REST API (stars, forks, and the repository a fork was made from), the Hugging Face Hub API (likes, downloads, and the base model a model was derived from) and DataCite (Zenodo and other data DOIs, and the GitHub release a Zenodo record archives), read again every month.

Cite this page

Scholar4AI. (2026). TuSimple/tusimple-benchmark: papers linking to it. Journal and Conference Research Rankings. Retrieved November 3, 2026, from https://scholar4ai.com/code/github-tusimple-tusimple-benchmark

@misc{scholar4ai-code-github-tusimple-tusimple-benchmark,
  author = {{Scholar4AI}},
  title = {TuSimple/tusimple-benchmark: papers linking to it},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/code/github-tusimple-tusimple-benchmark}},
  urldate = {2026-11-03},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}

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