Yu-Jhe Li

433 total citations · 1 hit paper
9 papers, 241 citations indexed

About

Yu-Jhe Li is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Yu-Jhe Li has authored 9 papers receiving a total of 241 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 2 papers in Aerospace Engineering. Recurrent topics in Yu-Jhe Li's work include Video Surveillance and Tracking Methods (3 papers), Human Pose and Action Recognition (3 papers) and Advanced Neural Network Applications (3 papers). Yu-Jhe Li is often cited by papers focused on Video Surveillance and Tracking Methods (3 papers), Human Pose and Action Recognition (3 papers) and Advanced Neural Network Applications (3 papers). Yu-Jhe Li collaborates with scholars based in United States, United Kingdom and Israel. Yu-Jhe Li's co-authors include Kris Kitani, Xinshuo Weng, Chih‐Yao Ma, BoRui Wu, Péter Vajda, Zijian He, Kan Chen, Xiaoliang Dai, Yen‐Cheng Liu and Matthew O’Toole and has published in prestigious journals such as 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) and 2021 IEEE/CVF International Conference on Computer Vision (ICCV).

In The Last Decade

Yu-Jhe Li

8 papers receiving 235 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.

Cross-Domain Adaptive Teacher for Object Detection

2022 139 citations Yu-Jhe Li, Xiaoliang Dai et al. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yu-Jhe Li United States	6	177	90	48	21	20	9	241
Mohammadreza Mostajabi Iran	3	282 1.6×	107 1.2×	36 0.8×	28 1.3×	15 0.8×	5	361
Gianluca Agresti Italy	10	187 1.1×	88 1.0×	25 0.5×	20 1.0×	14 0.7×	14	245
Wenqi Shao China	10	121 0.7×	97 1.1×	17 0.4×	17 0.8×	10 0.5×	37	231
Junhyuk Hyun South Korea	10	165 0.9×	70 0.8×	28 0.6×	20 1.0×	6 0.3×	18	211
Kevin J. Shih United States	7	318 1.8×	164 1.8×	46 1.0×	32 1.5×	7 0.3×	17	419
Tingfa Xu China	4	205 1.2×	64 0.7×	18 0.4×	30 1.4×	9 0.5×	6	239
Stavros Tsogkas Canada	8	191 1.1×	55 0.6×	30 0.6×	13 0.6×	22 1.1×	10	250
Seungeui Lee South Korea	4	178 1.0×	131 1.5×	44 0.9×	17 0.8×	15 0.8×	6	250
Nathan Drenkow United States	5	170 1.0×	33 0.4×	45 0.9×	41 2.0×	17 0.8×	13	232

Countries citing papers authored by Yu-Jhe Li

Since Specialization

Citations

This map shows the geographic impact of Yu-Jhe Li'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 Yu-Jhe Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu-Jhe Li more than expected).

Fields of papers citing papers by Yu-Jhe Li

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yu-Jhe Li. 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 Yu-Jhe Li. The network helps show where Yu-Jhe Li may publish in the future.

Co-authorship network of co-authors of Yu-Jhe Li

This figure shows the co-authorship network connecting the top 25 collaborators of Yu-Jhe Li. A scholar is included among the top collaborators of Yu-Jhe Li 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 Yu-Jhe Li. Yu-Jhe Li 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:

9 of 9 papers shown

1.

Li, Yu-Jhe, et al.. (2024). Flexible Depth Completion for Sparse and Varying Point Densities. 21540–21550.

2.

Li, Yu-Jhe, et al.. (2023). Azimuth Super-Resolution for FMCW Radar in Autonomous Driving. 17504–17513. 8 indexed citations

3.

Li, Yu-Jhe, Matthew O’Toole, & Kris Kitani. (2023). ST-MVDNet++: Improve Vehicle Detection with Lidar-Radar Geometrical Augmentation via Self-Training. 1–5. 4 indexed citations

4.

Li, Yu-Jhe, Xiaoliang Dai, Chih‐Yao Ma, et al.. (2022). Cross-Domain Adaptive Teacher for Object Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 7571–7580. 139 indexed citations breakdown →

5.

Li, Yu-Jhe, et al.. (2022). Modality-Agnostic Learning for Radar-Lidar Fusion in Vehicle Detection. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 908–917. 28 indexed citations

6.

Li, Yu-Jhe, Xinshuo Weng, & Kris Kitani. (2021). Learning Shape Representations for Person Re-Identification under Clothing Change. 35 indexed citations

7.

Xu, Yan, Yu-Jhe Li, Xinshuo Weng, & Kris Kitani. (2021). Wide-Baseline Multi-Camera Calibration using Person Re-Identification. 13129–13138. 16 indexed citations

8.

Li, Yu-Jhe, et al.. (2021). Crack Detection and Refinement Via Deep Reinforcement Learning. 529–533. 2 indexed citations

9.

Li, Yu-Jhe, Xinshuo Weng, Yan Xu, & Kris Kitani. (2021). Visio-Temporal Attention for Multi-Camera Multi-Target Association. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 9814–9824. 9 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.

Explore authors with similar magnitude of impact