Botian Shi

1.6k total citations · 1 hit paper
34 papers, 546 citations indexed

About

Botian Shi is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Botian Shi has authored 34 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 15 papers in Artificial Intelligence and 6 papers in Aerospace Engineering. Recurrent topics in Botian Shi's work include Advanced Neural Network Applications (9 papers), Multimodal Machine Learning Applications (8 papers) and Natural Language Processing Techniques (7 papers). Botian Shi is often cited by papers focused on Advanced Neural Network Applications (9 papers), Multimodal Machine Learning Applications (8 papers) and Natural Language Processing Techniques (7 papers). Botian Shi collaborates with scholars based in China, Hong Kong and United States. Botian Shi's co-authors include Yu Qiao, Zhendong Niu, Lei Ji, Nan Duan, Pinlong Cai, Daocheng Fu, Licheng Wen, Min Dou, Tao Chen and Xin Li and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing.

In The Last Decade

Botian Shi

24 papers receiving 529 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Drive Like a Human: Rethinking Autonomous Driving with Large Language Models

2024 82 citations Daocheng Fu, Licheng Wen et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Botian Shi China	12	317	164	84	78	42	34	546
Yiqi Zhong China	8	261 0.8×	122 0.7×	87 1.0×	100 1.3×	36 0.9×	12	459
Rohan Chandra United States	9	335 1.1×	129 0.8×	83 1.0×	67 0.9×	29 0.7×	19	493
Wenzhao Zheng China	12	483 1.5×	199 1.2×	82 1.0×	52 0.7×	33 0.8×	31	640
Yihan Hu China	4	263 0.8×	102 0.6×	87 1.0×	169 2.2×	28 0.7×	8	470
Aseem Behl Germany	6	328 1.0×	125 0.8×	80 1.0×	148 1.9×	38 0.9×	8	519
Liping Zheng China	13	245 0.8×	71 0.4×	61 0.7×	55 0.7×	18 0.4×	74	477
Jiankai Sun China	10	351 1.1×	167 1.0×	183 2.2×	70 0.9×	36 0.9×	23	662
Jirui Yuan China	7	291 0.9×	51 0.3×	91 1.1×	139 1.8×	65 1.5×	10	448
Guoqing Jin China	10	175 0.6×	125 0.8×	31 0.4×	50 0.6×	31 0.7×	34	420
Shao‐Wen Yang Taiwan	11	267 0.8×	86 0.5×	166 2.0×	52 0.7×	44 1.0×	26	475

Countries citing papers authored by Botian Shi

Since Specialization

Citations

This map shows the geographic impact of Botian Shi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Botian Shi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Botian Shi more than expected).

Fields of papers citing papers by Botian Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Botian Shi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Botian Shi. The network helps show where Botian Shi may publish in the future.

Co-authorship network of co-authors of Botian Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Botian Shi. A scholar is included among the top collaborators of Botian Shi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Botian Shi. Botian Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Liu, Qi, Hongbin Zhou, Zijun Chen, et al.. (2025). ChartX and ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning. IEEE Transactions on Image Processing. 34. 7436–7447.

2.

Chen, Runjian, Bo Zhang, Hongbin Zhou, et al.. (2025). SPOT: Scalable 3D Pre-Training via Occupancy Prediction for Learning Transferable 3D Representations. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(11). 9609–9625.

3.

Zhong, Ning, et al.. (2025). LeapVAD: A Leap in Autonomous Driving via Cognitive Perception and Dual-Process Thinking. IEEE Transactions on Neural Networks and Learning Systems. PP. 1–15.

4.

Chen, Zhe, Wei‐Yun Wang, S. Ye, et al.. (2025). Docopilot: Improving Multimodal Models for Document-Level Understanding. 4026–4037.

5.

Wang, Bin, et al.. (2025). Image Over Text: Transforming Formula Recognition Evaluation with Character Detection Matching. 19681–19690.

6.

Zhou, Hongbin, Jiawei Zhu, Xiaomeng Zhao, et al.. (2025). OmniDocBench: Benchmarking Diverse PDF Document Parsing with Comprehensive Annotations. 24838–24848.

7.

Li, Yikang, et al.. (2024). SensorX2Vehicle: Online Sensors-to-Vehicle Rotation Calibration Methods in Road Scenarios. IEEE Robotics and Automation Letters. 9(4). 3775–3782. 4 indexed citations

8.

Fu, Daocheng, Licheng Wen, Pinlong Cai, et al.. (2024). LimSim++: A Closed-Loop Platform for Deploying Multimodal LLMs in Autonomous Driving. 1084–1090. 16 indexed citations

9.

Zhang, Bo, et al.. (2024). Few-Shot Cross-Domain Object Detection With Instance-Level Prototype-Based Meta-Learning. IEEE Transactions on Circuits and Systems for Video Technology. 34(10). 9078–9089. 9 indexed citations

10.

Shi, Botian, et al.. (2024). Zero-training LiDAR-Camera Extrinsic Calibration Method Using Segment Anything Model. 14472–14478. 11 indexed citations

11.

Wang, Chengjie, et al.. (2024). An Extrinsic Calibration Method between LiDAR and GNSS/INS for Autonomous Driving. 14520–14526.

12.

Wen, Licheng, Pinlong Cai, Daocheng Fu, et al.. (2023). How drivers perform under different scenarios: Ability-related driving style extraction for large-scale dataset. Accident Analysis & Prevention. 196. 107445–107445. 8 indexed citations

13.

Xiang, Li, Junbo Yin, Botian Shi, et al.. (2023). LWSIS: LiDAR-Guided Weakly Supervised Instance Segmentation for Autonomous Driving. Proceedings of the AAAI Conference on Artificial Intelligence. 37(2). 1433–1441. 9 indexed citations

14.

Zhang, Bo, et al.. (2023). SUG: Single-dataset Unified Generalization for 3D Point Cloud Classification. 8644–8652. 7 indexed citations

15.

Xiang, Chao, Botian Shi, Hao Lü, et al.. (2023). Multi-Sensor Fusion and Cooperative Perception for Autonomous Driving: A Review. IEEE Intelligent Transportation Systems Magazine. 15(5). 36–58. 65 indexed citations

16.

Ma, Tao, Xuemeng Yang, Hongbin Zhou, et al.. (2023). DetZero: Rethinking Offboard 3D Object Detection with Long-term Sequential Point Clouds. 6713–6724. 24 indexed citations

17.

Zhang, Bo, et al.. (2023). Uni3D: A Unified Baseline for Multi-Dataset 3D Object Detection. 9253–9262. 26 indexed citations

18.

Tu, Rong-Cheng, Lei Ji, Huaishao Luo, et al.. (2021). Hashing based Efficient Inference for Image-Text Matching. 743–752. 8 indexed citations

19.

Shi, Botian, Lei Ji, Zhendong Niu, et al.. (2020). Learning Semantic Concepts and Temporal Alignment for Narrated Video Procedural Captioning. 4355–4363. 11 indexed citations

20.

Shi, Botian, Lei Ji, Yaobo Liang, et al.. (2019). Dense Procedure Captioning in Narrated Instructional Videos. 6382–6391. 44 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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