Bin-Bin Gao

1.7k total citations · 1 hit paper
27 papers, 844 citations indexed

About

Bin-Bin Gao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Control and Systems Engineering. According to data from OpenAlex, Bin-Bin Gao has authored 27 papers receiving a total of 844 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 5 papers in Control and Systems Engineering. Recurrent topics in Bin-Bin Gao's work include Advanced Image and Video Retrieval Techniques (11 papers), Domain Adaptation and Few-Shot Learning (11 papers) and Anomaly Detection Techniques and Applications (6 papers). Bin-Bin Gao is often cited by papers focused on Advanced Image and Video Retrieval Techniques (11 papers), Domain Adaptation and Few-Shot Learning (11 papers) and Anomaly Detection Techniques and Applications (6 papers). Bin-Bin Gao collaborates with scholars based in China, United Kingdom and Taiwan. Bin-Bin Gao's co-authors include Jianxin Wu, Xin Geng, Hong-Yu Zhou, Chao Xing, Chen-Wei Xie, Chengjie Wang, Xiu-Shen Wei, Xu Yang, Ying Zhou and Jianjun Wang and has published in prestigious journals such as IEEE Transactions on Image Processing, Pattern Recognition and IEEE Transactions on Multimedia.

In The Last Decade

Bin-Bin Gao

26 papers receiving 823 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.

Deep Label Distribution Learning With Label Ambiguity

2017 349 citations Bin-Bin Gao, Chao Xing et al. IEEE Transactions on Image Processing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bin-Bin Gao China	12	548	441	120	57	50	27	844
Chen-Wei Xie China	7	593 1.1×	429 1.0×	70 0.6×	44 0.8×	53 1.1×	12	857
Yikui Zhai China	15	354 0.6×	144 0.3×	114 0.9×	54 0.9×	38 0.8×	103	698
Golnaz Ghiasi United States	10	512 0.9×	227 0.5×	56 0.5×	59 1.0×	54 1.1×	13	629
Yunjey Choi South Korea	5	970 1.8×	211 0.5×	68 0.6×	58 1.0×	43 0.9×	6	1.1k
Peiran Ren China	16	1.1k 2.0×	103 0.2×	134 1.1×	102 1.8×	26 0.5×	32	1.2k
Yunlian Sun China	12	430 0.8×	199 0.5×	107 0.9×	36 0.6×	18 0.4×	26	624
Yunfan Liu China	13	563 1.0×	163 0.4×	65 0.5×	23 0.4×	57 1.1×	38	780
Piotr Mardziel United States	8	322 0.6×	520 1.2×	67 0.6×	43 0.8×	135 2.7×	12	906
Zi-Rui Wang China	11	294 0.5×	374 0.8×	71 0.6×	73 1.3×	49 1.0×	23	661

Countries citing papers authored by Bin-Bin Gao

Since Specialization

Citations

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

Fields of papers citing papers by Bin-Bin Gao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Bin-Bin Gao. 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 Bin-Bin Gao. The network helps show where Bin-Bin Gao may publish in the future.

Co-authorship network of co-authors of Bin-Bin Gao

This figure shows the co-authorship network connecting the top 25 collaborators of Bin-Bin Gao. A scholar is included among the top collaborators of Bin-Bin Gao 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 Bin-Bin Gao. Bin-Bin Gao 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.

Zhou, Ziqing, Chengjie Wang, Yongxin Pan, et al.. (2025). Real-IAD D³: A Real-World 2D/Pseudo-3D/3D Dataset for Industrial Anomaly Detection. 15214–15223.

2.

Wang, Chengjie, et al.. (2024). SoftPatch+: Fully unsupervised anomaly classification and segmentation. Pattern Recognition. 161. 111295–111295. 4 indexed citations

3.

Gao, Bin-Bin, Yi Zeng, Xin Tan, et al.. (2024). Learning Task-Aware Language-Image Representation for Class-Incremental Object Detection. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 7096–7104. 2 indexed citations

4.

Liu, Jiaqi, Kai Wu, Huiling Chen, et al.. (2024). Unsupervised Continual Anomaly Detection with Contrastively-Learned Prompt. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3639–3647. 11 indexed citations

5.

Wang, Chengjie, Bin-Bin Gao, Jiangning Zhang, et al.. (2024). Real-IAD: A Real-World Multi-View Dataset for Benchmarking Versatile Industrial Anomaly Detection. 22883–22892. 25 indexed citations

6.

Yang, Siqian, et al.. (2023). Clustered-patch Element Connection for Few-shot Learning. 991–998. 7 indexed citations

7.

Yang, Siqian, Tom Wu, Guannan Jiang, et al.. (2023). SpatialFormer: Semantic and Target Aware Attentions for Few-Shot Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(7). 8430–8437. 10 indexed citations

8.

Wang, Guohua, Bin-Bin Gao, & Chengjie Wang. (2023). How to Reduce Change Detection to Semantic Segmentation. Pattern Recognition. 138. 109384–109384. 17 indexed citations

9.

Gao, Bin-Bin, Bizhong Xia, Jinbao Wang, et al.. (2023). Cross-Modal Alternating Learning With Task-Aware Representations for Continual Learning. IEEE Transactions on Multimedia. 26. 5911–5924. 10 indexed citations

10.

Chen, Jiacheng, Bin-Bin Gao, Zongqing Lu, et al.. (2022). APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation. IEEE Transactions on Multimedia. 25. 4361–4373. 30 indexed citations

11.

Wang, Jinbao, Bizhong Xia, Bin-Bin Gao, et al.. (2022). Towards Continual Adaptation in Industrial Anomaly Detection. Proceedings of the 30th ACM International Conference on Multimedia. 2871–2880. 11 indexed citations

12.

Liu, Jun, Guannan Jiang, Xi Wang, et al.. (2022). Global Meets Local: Effective Multi-Label Image Classification via Category-Aware Weak Supervision. Proceedings of the 30th ACM International Conference on Multimedia. 6318–6326. 3 indexed citations

13.

Wang, Changan, et al.. (2022). HDNet: A Hierarchically Decoupled Network for Crowd Counting. 2022 IEEE International Conference on Multimedia and Expo (ICME). 1–6. 2 indexed citations

14.

Gao, Bin-Bin, Hong-Yu Zhou, Jianxin Wu, & Xin Geng. (2018). Age Estimation Using Expectation of Label Distribution Learning. 712–718. 111 indexed citations

15.

Zhou, Hong-Yu, Bin-Bin Gao, & Jianxin Wu. (2017). Adaptive Feeding: Achieving Fast and Accurate Detections by Adaptively Combining Object Detectors. 3525–3533. 18 indexed citations

16.

Gao, Bin-Bin, Chao Xing, Chen-Wei Xie, Jianxin Wu, & Xin Geng. (2017). Deep Label Distribution Learning With Label Ambiguity. IEEE Transactions on Image Processing. 26(6). 2825–2838. 349 indexed citations breakdown →

17.

Zhou, Hong-Yu, Bin-Bin Gao, & Jianxin Wu. (2017). Sunrise or Sunset: Selective Comparison Learning for Subtle Attribute Recognition. 6 indexed citations

18.

Wei, Xiu-Shen, Bin-Bin Gao, & Jianxin Wu. (2015). Deep Spatial Pyramid Ensemble for Cultural Event Recognition. 280–286. 22 indexed citations

19.

Yang, Xu, Bin-Bin Gao, Chao Xing, et al.. (2015). Deep Label Distribution Learning for Apparent Age Estimation. 344–350. 69 indexed citations

20.

Gao, Bin-Bin, et al.. (2015). Coordinate Descent Fuzzy Twin Support Vector Machine for Classification. 7–12. 25 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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