Robby T. Tan

2.3k total citations · 1 hit paper
39 papers, 1.2k citations indexed

About

Robby T. Tan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Atomic and Molecular Physics, and Optics. According to data from OpenAlex, Robby T. Tan has authored 39 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Computer Vision and Pattern Recognition, 12 papers in Artificial Intelligence and 6 papers in Atomic and Molecular Physics, and Optics. Recurrent topics in Robby T. Tan's work include Image Enhancement Techniques (17 papers), Advanced Vision and Imaging (10 papers) and Video Surveillance and Tracking Methods (7 papers). Robby T. Tan is often cited by papers focused on Image Enhancement Techniques (17 papers), Advanced Vision and Imaging (10 papers) and Video Surveillance and Tracking Methods (7 papers). Robby T. Tan collaborates with scholars based in Singapore, China and Hong Kong. Robby T. Tan's co-authors include Wenhan Yang, Jiaying Liu, Shiqi Wang, Jiashi Feng, Shuicheng Yan, Zongming Guo, Aashish Sharma, Yuming Fang, Yeying Jin and Katsushi Ikeuchi and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition and IEEE Transactions on Circuits and Systems for Video Technology.

In The Last Decade

Robby T. Tan

37 papers receiving 1.1k citations

Hit Papers

Joint Rain Detection and ... 2019 2026 2021 2023 2019 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robby T. Tan Singapore 17 988 239 106 65 63 39 1.2k
Li-Wei Kang Taiwan 13 1.2k 1.2× 415 1.7× 43 0.4× 65 1.0× 66 1.0× 32 1.3k
Shuo Zhang China 16 913 0.9× 229 1.0× 73 0.7× 25 0.4× 6 0.1× 57 1.1k
Ning Xu China 13 781 0.8× 115 0.5× 125 1.2× 48 0.7× 8 0.1× 58 976
Didier Aubert France 14 1.3k 1.3× 587 2.5× 39 0.4× 54 0.8× 134 2.1× 38 1.5k
Xudong Li China 16 684 0.7× 126 0.5× 199 1.9× 9 0.1× 52 0.8× 68 831
Zhanghan Ke Hong Kong 6 542 0.5× 140 0.6× 206 1.9× 21 0.3× 25 0.4× 10 858
Yuchen Fan China 14 1.6k 1.6× 772 3.2× 94 0.9× 25 0.4× 7 0.1× 47 1.9k
Ruizhi Qiao China 8 678 0.7× 262 1.1× 115 1.1× 23 0.4× 65 1.0× 18 843

Countries citing papers authored by Robby T. Tan

Since Specialization
Citations

This map shows the geographic impact of Robby T. Tan'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 Robby T. Tan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Robby T. Tan more than expected).

Fields of papers citing papers by Robby T. Tan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Robby T. Tan. 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 Robby T. Tan. The network helps show where Robby T. Tan may publish in the future.

Co-authorship network of co-authors of Robby T. Tan

This figure shows the co-authorship network connecting the top 25 collaborators of Robby T. Tan. A scholar is included among the top collaborators of Robby T. Tan 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 Robby T. Tan. Robby T. Tan 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.
Yan, Wending, et al.. (2024). Semantic Segmentation in Multiple Adverse Weather Conditions with Domain Knowledge Retention. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 6558–6566. 1 indexed citations
2.
Yue, Xianghu, Xiaoxue Gao, Chen Zhang, et al.. (2024). Beyond Single-Audio: Advancing Multi-Audio Processing in Audio Large Language Models. 10917–10930.
3.
Lin, Beibei, Yeying Jin, Wending Yan, et al.. (2024). NightRain: Nighttime Video Deraining via Adaptive-Rain-Removal and Adaptive-Correction. Proceedings of the AAAI Conference on Artificial Intelligence. 38(4). 3378–3385. 4 indexed citations
4.
Xie, Jinheng, et al.. (2024). HEAP: Unsupervised Object Discovery and Localization with Contrastive Grouping. Proceedings of the AAAI Conference on Artificial Intelligence. 38(7). 7323–7331. 1 indexed citations
5.
Wang, Jiadong, Zexu Pan, Malu Zhang, Robby T. Tan, & Haizhou Li. (2024). Restoring Speaking Lips from Occlusion for Audio-Visual Speech Recognition. Proceedings of the AAAI Conference on Artificial Intelligence. 38(17). 19144–19152. 3 indexed citations
6.
Jin, Yeying, Wei Ye, Wenhan Yang, Yuan Yuan, & Robby T. Tan. (2024). DeS3: Adaptive Attention-Driven Self and Soft Shadow Removal Using ViT Similarity. Proceedings of the AAAI Conference on Artificial Intelligence. 38(3). 2634–2642. 6 indexed citations
7.
Wang, Jiangang, et al.. (2024). CAT: Exploiting Inter-Class Dynamics for Domain Adaptive Object Detection. 16541–16550. 8 indexed citations
8.
Wang, Jian-Gang, et al.. (2023). 2PCNet: Two-Phase Consistency Training for Day-to-Night Unsupervised Domain Adaptive Object Detection. 11484–11493. 29 indexed citations
9.
Chen, Yiming, Simin Chen, Zexin Li, et al.. (2023). Dynamic Transformers Provide a False Sense of Efficiency. 5 indexed citations
10.
Yang, Wenhan, Robby T. Tan, Shiqi Wang, Alex C. Kot, & Jiaying Liu. (2022). Learning to Remove Rain in Video With Self-Supervision. IEEE Transactions on Pattern Analysis and Machine Intelligence. 46(3). 1378–1396. 6 indexed citations
11.
Liu, Lu & Robby T. Tan. (2021). Human object interaction detection using two-direction spatial enhancement and exclusive object prior. Pattern Recognition. 124. 108438–108438. 8 indexed citations
12.
Yang, Wenhan, Robby T. Tan, Jiashi Feng, et al.. (2021). Recurrent Multi-Frame Deraining: Combining Physics Guidance and Adversarial Learning. IEEE Transactions on Pattern Analysis and Machine Intelligence. 44(11). 1–1. 34 indexed citations
13.
Tan, Robby T., et al.. (2021). Continuous-time Radar-inertial Odometry for Automotive Radars. 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). 323–330. 32 indexed citations
14.
Yang, Wenhan, Robby T. Tan, Shiqi Wang, & Jiaying Liu. (2020). Self-Learning Video Rain Streak Removal: When Cyclic Consistency Meets Temporal Correspondence. 1717–1726. 52 indexed citations
15.
Yang, Wenhan, Robby T. Tan, Shiqi Wang, Yuming Fang, & Jiaying Liu. (2020). Single Image Deraining: From Model-Based to Data-Driven and Beyond. IEEE Transactions on Pattern Analysis and Machine Intelligence. 43(11). 4059–4077. 194 indexed citations
16.
Liu, Lu, et al.. (2019). Certainty-Driven Consistency Loss for Semi-supervised Learning. National University of Singapore. 2 indexed citations
17.
Guo, Jiaming, Loong‐Fah Cheong, & Robby T. Tan. (2016). Video Foreground Cosegmentation Based on Common Fate. IEEE Transactions on Circuits and Systems for Video Technology. 28(3). 586–600. 4 indexed citations
18.
Tan, Robby T., Ko Nishino, & Katsushi Ikeuchi. (2004). Separating reflection components based on chromaticity and noise analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence. 26(10). 1373–1379. 57 indexed citations
19.
Tan, Robby T., Ko Nishino, & Katsushi Ikeuchi. (2002). Separating Diffuse and Specular Reflection Components based on Surface Color Ratio and Chromaticity. Machine Vision and Applications. 14–19. 3 indexed citations
20.
Tan, Robby T., Ko Nishino, & Katsushi Ikeuchi. (2002). Reflection Components Separation using Chromaticity and Noise Analysis. Lupus. 32(14). 1686–1688. 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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