Loong‐Fah Cheong

3.6k total citations
66 papers, 2.1k citations indexed

About

Loong‐Fah Cheong is a scholar working on Computer Vision and Pattern Recognition, Aerospace Engineering and Artificial Intelligence. According to data from OpenAlex, Loong‐Fah Cheong has authored 66 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 61 papers in Computer Vision and Pattern Recognition, 15 papers in Aerospace Engineering and 8 papers in Artificial Intelligence. Recurrent topics in Loong‐Fah Cheong's work include Advanced Vision and Imaging (42 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Optical measurement and interference techniques (16 papers). Loong‐Fah Cheong is often cited by papers focused on Advanced Vision and Imaging (42 papers), Advanced Image and Video Retrieval Techniques (17 papers) and Optical measurement and interference techniques (16 papers). Loong‐Fah Cheong collaborates with scholars based in Singapore, United States and China. Loong‐Fah Cheong's co-authors include Hee Lin Wang, Robby T. Tan, Shuicheng Yan, Ju Sun, Ruoteng Li, Zhuwen Li, Nianjuan Jiang, Tat‐Seng Chua, Ping Tan and Steven Zhiying Zhou and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing and ACM Transactions on Graphics.

In The Last Decade

Loong‐Fah Cheong

62 papers receiving 2.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Loong‐Fah Cheong Singapore 25 1.9k 330 315 224 142 66 2.1k
Tat‐Jen Cham Singapore 23 1.8k 1.0× 174 0.5× 369 1.2× 257 1.1× 222 1.6× 86 2.1k
Joon‐Young Lee South Korea 27 2.0k 1.1× 237 0.7× 254 0.8× 328 1.5× 99 0.7× 70 2.4k
Tonmoy Saikia Germany 4 1.7k 0.9× 246 0.7× 326 1.0× 253 1.1× 110 0.8× 4 2.0k
Steve Maybank United Kingdom 18 1.2k 0.6× 213 0.6× 299 0.9× 102 0.5× 96 0.7× 31 1.4k
Dimitrios Zarpalas Greece 24 1.1k 0.6× 434 1.3× 134 0.4× 156 0.7× 113 0.8× 85 1.6k
Alexander Sorkine‐Hornung United States 20 2.8k 1.5× 173 0.5× 163 0.5× 385 1.7× 68 0.5× 37 3.0k
João Carreira United States 18 1.6k 0.9× 338 1.0× 349 1.1× 133 0.6× 51 0.4× 30 1.9k
Esther Koller-Meier Switzerland 15 2.1k 1.1× 416 1.3× 555 1.8× 198 0.9× 159 1.1× 28 2.4k
Federico Perazzi United States 17 3.8k 2.0× 223 0.7× 312 1.0× 455 2.0× 81 0.6× 22 4.0k
Jian Zhao China 28 1.7k 0.9× 267 0.8× 567 1.8× 78 0.3× 134 0.9× 109 2.3k

Countries citing papers authored by Loong‐Fah Cheong

Since Specialization
Citations

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

Fields of papers citing papers by Loong‐Fah Cheong

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Loong‐Fah Cheong. 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 Loong‐Fah Cheong. The network helps show where Loong‐Fah Cheong may publish in the future.

Co-authorship network of co-authors of Loong‐Fah Cheong

This figure shows the co-authorship network connecting the top 25 collaborators of Loong‐Fah Cheong. A scholar is included among the top collaborators of Loong‐Fah Cheong 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 Loong‐Fah Cheong. Loong‐Fah Cheong 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.
Xu, Xun, Le Zhang, Loong‐Fah Cheong, Zhuwen Li, & Ce Zhu. (2021). Learning Clustering for Motion Segmentation. IEEE Transactions on Circuits and Systems for Video Technology. 32(3). 908–919. 14 indexed citations
2.
Zhuang, Bingbing, Quoc-Huy Tran, Pan Ji, Loong‐Fah Cheong, & Manmohan Chandraker. (2019). Learning Structure-And-Motion-Aware Rolling Shutter Correction. 4546–4555. 34 indexed citations
3.
Jiang, Nianjuan, et al.. (2017). Direct Photometric Alignment by Mesh Deformation. 2701–2709. 37 indexed citations
4.
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
5.
Cheong, Loong‐Fah, et al.. (2016). Minimal Basis Subspace Representation: A Unified Framework for Rigid and Non-rigid Motion Segmentation. International Journal of Computer Vision. 121(2). 209–233. 5 indexed citations
6.
Li, Zhuwen, Ping Tan, Robby T. Tan, et al.. (2015). Simultaneous video defogging and stereo reconstruction. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 4988–4997. 95 indexed citations
7.
Lin, Wen-Yan, Siying Liu, Yasuyuki Matsushita, Tian-Tsong Ng, & Loong‐Fah Cheong. (2011). Smoothly varying affine stitching. National University of Singapore. 345–352. 204 indexed citations
8.
Sun, Ju, et al.. (2010). Robust Low-Rank Subspace Segmentation with Semidefinite Guarantees. National University of Singapore. 1179–1188. 41 indexed citations
9.
Zhong, Huiying, et al.. (2010). Tilt perception from optic flow in two-view stimuli. Journal of Vision. 1(3). 315–315.
10.
Sun, Ju, Xiao Wu, Shuicheng Yan, et al.. (2009). Hierarchical spatio-temporal context modeling for action recognition. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 2004–2011. 245 indexed citations
11.
Cheong, Loong‐Fah, et al.. (2007). What do we perceive from motion pictures? A computational account. Journal of the Optical Society of America A. 24(6). 1485–1485. 2 indexed citations
12.
Yu, Xinguo, Nianjuan Jiang, & Loong‐Fah Cheong. (2007). Accurate and Stable Camera Calibration of Broadcast Tennis Video. National University of Singapore. III – 93. 3 indexed citations
13.
Mittal, A. & Loong‐Fah Cheong. (2006). Formulation and Use of Time-to-Collision in Content-Based Retrieval. Americanae (AECID Library). 1 indexed citations
14.
Zhong, Huiying, et al.. (2006). The visual perception of plane tilt from motion in small field and large field: Psychophysics and theory. Vision Research. 46(20). 3494–3513. 6 indexed citations
15.
Panerai, Francesco, et al.. (2002). Absolute distance perception during in-depth head movement: calibrating optic flow with extra-retinal information. Vision Research. 42(16). 1991–2003. 19 indexed citations
16.
Cheong, Loong‐Fah & Yiannis Aloimonos. (2002). Iso-distortion contours and egomotion estimation. 55–60.
17.
Cheong, Loong‐Fah, et al.. (2002). Synergizing spatial and temporal texture. IEEE Transactions on Image Processing. 11(10). 1179–1191. 54 indexed citations
18.
Cheong, Loong‐Fah. (2000). Scene-Based Shot Change Detection and Comparative Evaluation. Computer Vision and Image Understanding. 79(2). 224–235. 6 indexed citations
19.
Cheong, Loong‐Fah, et al.. (1999). Geometry of Distorted Visual Space and Cremona Transformation. International Journal of Computer Vision. 32(3). 195–212. 7 indexed citations
20.
Fermüller, Cornelia, Loong‐Fah Cheong, & Yiannis Aloimonos. (1997). Visual space distortion. Biological Cybernetics. 77(5). 323–337. 13 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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