Xingping Dong

3.3k total citations
30 papers, 1.9k citations indexed

About

Xingping Dong is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Xingping Dong has authored 30 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Computer Vision and Pattern Recognition, 7 papers in Artificial Intelligence and 3 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Xingping Dong's work include Advanced Image and Video Retrieval Techniques (11 papers), Video Surveillance and Tracking Methods (10 papers) and Visual Attention and Saliency Detection (8 papers). Xingping Dong is often cited by papers focused on Advanced Image and Video Retrieval Techniques (11 papers), Video Surveillance and Tracking Methods (10 papers) and Visual Attention and Saliency Detection (8 papers). Xingping Dong collaborates with scholars based in China, United Arab Emirates and Macao. Xingping Dong's co-authors include Jianbing Shen, Ling Shao, Wenguan Wang, Jianbing Shen, Ali Borji, Fatih Porikli, Luc Van Gool, Ruigang Yang, Xin Tang and Steven C. H. Hoi and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Geoscience and Remote Sensing and IEEE Transactions on Image Processing.

In The Last Decade

Xingping Dong

28 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Xingping Dong China 20 1.6k 296 211 177 147 30 1.9k
Xiankai Lu China 21 1.9k 1.2× 428 1.4× 197 0.9× 373 2.1× 111 0.8× 61 2.3k
Shengfeng He China 31 2.9k 1.9× 521 1.8× 210 1.0× 595 3.4× 88 0.6× 158 3.5k
Jae-Yeal Nam South Korea 20 1.0k 0.7× 162 0.5× 86 0.4× 126 0.7× 571 3.9× 56 1.4k
Suha Kwak South Korea 20 1.8k 1.2× 971 3.3× 132 0.6× 172 1.0× 89 0.6× 53 2.3k
Xuemiao Xu China 21 1.3k 0.8× 313 1.1× 92 0.4× 238 1.3× 39 0.3× 83 1.9k
Hongkai Yu United States 22 1.3k 0.8× 438 1.5× 196 0.9× 249 1.4× 75 0.5× 85 1.9k
Chenglizhao Chen China 28 1.8k 1.2× 287 1.0× 115 0.5× 398 2.2× 41 0.3× 92 2.1k
Qing Guo China 23 1.7k 1.1× 580 2.0× 299 1.4× 190 1.1× 239 1.6× 119 2.3k
Lingxiao Yang China 9 854 0.6× 178 0.6× 104 0.5× 160 0.9× 41 0.3× 23 1.2k

Countries citing papers authored by Xingping Dong

Since Specialization
Citations

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

Fields of papers citing papers by Xingping Dong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Xingping Dong. 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 Xingping Dong. The network helps show where Xingping Dong may publish in the future.

Co-authorship network of co-authors of Xingping Dong

This figure shows the co-authorship network connecting the top 25 collaborators of Xingping Dong. A scholar is included among the top collaborators of Xingping Dong 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 Xingping Dong. Xingping Dong is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Dong, Xingping, et al.. (2025). Condition-Guided Diffusion for Multi-Modal Pedestrian Trajectory Prediction Incorporating Intention and Interaction Priors. IEEE Transactions on Pattern Analysis and Machine Intelligence. 48(4). 4406–4419.
2.
Dong, Xingping, et al.. (2025). Semantic-Aware Pseudo-Labeling for Unsupervised Meta-Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(7). 5475–5488. 1 indexed citations
3.
Ye, Mang, et al.. (2025). Perception Assisted Transformer for Unsupervised Object Re-Identification. IEEE Transactions on Image Processing. 34. 2112–2123. 1 indexed citations
4.
Liu, Mengjie, et al.. (2025). A Deep Learning-Based Precipitation Nowcasting Model Fusing GNSS-PWV and Radar Echo Observations. IEEE Transactions on Geoscience and Remote Sensing. 63. 1–9. 3 indexed citations
5.
Dong, Xingping, et al.. (2024). High-Fidelity and High-Efficiency Talking Portrait Synthesis With Detail-Aware Neural Radiance Fields. IEEE Transactions on Visualization and Computer Graphics. 31(9). 6022–6035.
6.
Dong, Xingping, et al.. (2024). Pseudo-Labeling Based Practical Semi-Supervised Meta-Training for Few-Shot Learning. IEEE Transactions on Image Processing. 33. 5663–5675. 6 indexed citations
7.
Han, Wencheng, et al.. (2023). Referring Multi-Object Tracking. 14633–14642. 45 indexed citations
8.
Wu, Dongming, Xingping Dong, Ling Shao, & Jianbing Shen. (2022). Multi-Level Representation Learning with Semantic Alignment for Referring Video Object Segmentation. 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). 4986–4995. 39 indexed citations
9.
Dong, Xingping, et al.. (2021). Learning to Fuse Asymmetric Feature Maps in Siamese Trackers. 16565–16575. 62 indexed citations
10.
Wu, Dongming, Xingping Dong, Jianbing Shen, & Steven C. H. Hoi. (2020). Reducing Estimation Bias via Triplet-Average Deep Deterministic Policy Gradient. IEEE Transactions on Neural Networks and Learning Systems. 31(11). 4933–4945. 63 indexed citations
11.
Wang, Wenguan, Jianbing Shen, Xingping Dong, Ali Borji, & Ruigang Yang. (2019). Inferring Salient Objects from Human Fixations. IEEE Transactions on Pattern Analysis and Machine Intelligence. 42(8). 1913–1927. 188 indexed citations
12.
Dong, Xingping, Jianbing Shen, Wenguan Wang, et al.. (2019). Dynamical Hyperparameter Optimization via Deep Reinforcement Learning in Tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(5). 1515–1529. 168 indexed citations
13.
Wang, Hui, Jianbing Shen, Junbo Yin, et al.. (2019). Adaptive Nonlocal Random Walks for Image Superpixel Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. 30(3). 822–834. 19 indexed citations
14.
Wang, Wenguan, Jianbing Shen, Xingping Dong, & Ali Borji. (2018). Salient Object Detection Driven by Fixation Prediction. Journal of International Crisis and Risk Communication Research. 1711–1720. 166 indexed citations
15.
Dong, Xingping, Jianbing Shen, & Fatih Porikli. (2017). Quadruplet Network with One-Shot Learning for Visual Tracking.. arXiv (Cornell University). 1 indexed citations
16.
Shen, Jianbing, Jianteng Peng, Xingping Dong, Ling Shao, & Fatih Porikli. (2017). Higher Order Energies for Image Segmentation. IEEE Transactions on Image Processing. 26(10). 4911–4922. 68 indexed citations
17.
Liang, Yuling, Jianbing Shen, Xingping Dong, Hanqiu Sun, & Xuelong Li. (2015). Video Supervoxels Using Partially Absorbing Random Walks. IEEE Transactions on Circuits and Systems for Video Technology. 26(5). 928–938. 37 indexed citations
18.
Dong, Xingping, Jianbing Shen, Ling Shao, & Shuicheng Yan. (2015). Interactive Cosegmentation Using Global and Local Energy Optimization. IEEE Transactions on Image Processing. 24(11). 3966–3977. 61 indexed citations
19.
Dong, Xingping, Jianbing Shen, Ling Shao, & Luc Van Gool. (2015). Sub-Markov Random Walk for Image Segmentation. IEEE Transactions on Image Processing. 25(2). 516–527. 165 indexed citations
20.
Liang, Yuling, Xingping Dong, & Jianbing Shen. (2014). Supervoxel using random walks. 120–124. 1 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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