Ser-Nam Lim

3.8k total citations
55 papers, 1.3k citations indexed

About

Ser-Nam Lim is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Aerospace Engineering. According to data from OpenAlex, Ser-Nam Lim has authored 55 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Computer Vision and Pattern Recognition, 27 papers in Artificial Intelligence and 5 papers in Aerospace Engineering. Recurrent topics in Ser-Nam Lim's work include Domain Adaptation and Few-Shot Learning (19 papers), Advanced Neural Network Applications (16 papers) and Multimodal Machine Learning Applications (16 papers). Ser-Nam Lim is often cited by papers focused on Domain Adaptation and Few-Shot Learning (19 papers), Advanced Neural Network Applications (16 papers) and Multimodal Machine Learning Applications (16 papers). Ser-Nam Lim collaborates with scholars based in United States, Israel and China. Ser-Nam Lim's co-authors include Abhinav Shrivastava, Larry S. Davis, Serge Belongie, Nils Krahnstoever, Ting Yu, Xintong Han, Kedar A. Patwardhan, L.S. Davis, Kilian Q. Weinberger and Xitong Yang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Multimedia Systems and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Ser-Nam Lim

50 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ser-Nam Lim United States 20 984 598 172 85 79 55 1.3k
Anthony Hoogs United States 20 1.1k 1.1× 440 0.7× 119 0.7× 83 1.0× 160 2.0× 79 1.3k
Tom Duerig United States 6 1.1k 1.1× 631 1.1× 87 0.5× 49 0.6× 76 1.0× 6 1.5k
Shikui Wei China 19 1.2k 1.2× 412 0.7× 140 0.8× 60 0.7× 95 1.2× 78 1.5k
Mircea Cimpoi United Kingdom 5 1.5k 1.5× 776 1.3× 214 1.2× 53 0.6× 141 1.8× 6 2.0k
Xiaodong Gu China 19 741 0.8× 386 0.6× 135 0.8× 134 1.6× 37 0.5× 96 1.2k
Harish Bhaskar United Arab Emirates 16 649 0.7× 307 0.5× 178 1.0× 51 0.6× 64 0.8× 62 929
Yongjian Wu China 27 2.3k 2.4× 1.0k 1.7× 115 0.7× 84 1.0× 101 1.3× 71 2.7k
Yuan He China 19 1.0k 1.1× 639 1.1× 112 0.7× 141 1.7× 82 1.0× 58 1.5k
Brian McWilliams Switzerland 12 1.7k 1.7× 247 0.4× 222 1.3× 53 0.6× 81 1.0× 22 2.0k
Christopher Olah United States 3 845 0.9× 497 0.8× 84 0.5× 103 1.2× 24 0.3× 3 1.3k

Countries citing papers authored by Ser-Nam Lim

Since Specialization
Citations

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

Fields of papers citing papers by Ser-Nam Lim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ser-Nam Lim. 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 Ser-Nam Lim. The network helps show where Ser-Nam Lim may publish in the future.

Co-authorship network of co-authors of Ser-Nam Lim

This figure shows the co-authorship network connecting the top 25 collaborators of Ser-Nam Lim. A scholar is included among the top collaborators of Ser-Nam Lim 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 Ser-Nam Lim. Ser-Nam Lim 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.
Liu, Yexin, et al.. (2025). Unveiling the Ignorance of MLLMs: Seeing Clearly, Answering Incorrectly. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 9087–9097.
2.
3.
Li, Yali, Xi Chen, Ser-Nam Lim, et al.. (2024). UniDetector: Towards Universal Object Detection With Heterogeneous Supervision. IEEE Transactions on Pattern Analysis and Machine Intelligence. 47(7). 5205–5222. 2 indexed citations
4.
Han, Guangxing & Ser-Nam Lim. (2024). Few-Shot Object Detection with Foundation Models. 28608–28618. 19 indexed citations
5.
He, Bo, Hengduo Li, Menglin Jia, et al.. (2024). MA-LMM: Memory-Augmented Large Multimodal Model for Long-Term Video Understanding. 13504–13514. 19 indexed citations
6.
Geiping, Jonas, et al.. (2024). Object Recognition as Next Token Prediction. 16645–16656. 1 indexed citations
7.
Lim, Ser-Nam, et al.. (2024). On the Robustness of Large Multimodal Models Against Image Adversarial Attacks. 24625–24634. 9 indexed citations
8.
Wang, Zhenyu, Yali Li, Xi Chen, et al.. (2023). Detecting Everything in the Open World: Towards Universal Object Detection. 11433–11443. 55 indexed citations
9.
Pinto, Francesco, et al.. (2023). Sample-Dependent Adaptive Temperature Scaling for Improved Calibration. Proceedings of the AAAI Conference on Artificial Intelligence. 37(12). 14919–14926. 7 indexed citations
10.
Prabhu, Ameya, Hasan Abed Al Kader Hammoud, Puneet K. Dokania, et al.. (2023). Computationally Budgeted Continual Learning: What Does Matter?. King Abdullah University of Science and Technology Repository (King Abdullah University of Science and Technology). 3698–3707. 21 indexed citations
11.
Chen, Xi, Shuang Li, Ser-Nam Lim, Antonio Torralba, & Hengshuang Zhao. (2023). Open-vocabulary Panoptic Segmentation with Embedding Modulation. 1141–1150. 9 indexed citations
12.
Zhou, Yipin & Ser-Nam Lim. (2021). Joint Audio-Visual Deepfake Detection. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 14780–14789.
13.
Davis, Larry S., et al.. (2021). Analyzing and Mitigating JPEG Compression Defects in Deep Learning. 2357–2367. 20 indexed citations
14.
Huang, Qian, et al.. (2021). Combining Label Propagation and Simple Models out-performs Graph Neural Networks. arXiv (Cornell University). 2 indexed citations
15.
Jia, Menglin, Zuxuan Wu, Austin Reiter, et al.. (2021). Exploring Visual Engagement Signals for Representation Learning. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 4186–4197. 4 indexed citations
16.
Luo, Wei, Xitong Yang, Yuheng Lu, et al.. (2019). Cross-X Learning for Fine-Grained Visual Categorization. 8241–8250. 170 indexed citations
17.
Chen, Bor-Chun, Larry S. Davis, & Ser-Nam Lim. (2019). An Analysis of Object Embeddings for Image Retrieval.. arXiv (Cornell University). 3 indexed citations
18.
Sankaranarayanan, Swami, Yogesh Balaji, Arpit Jain, Ser-Nam Lim, & Rama Chellappa. (2017). Unsupervised Domain Adaptation for Semantic Segmentation with GANs.. arXiv (Cornell University). 26 indexed citations
19.
Chang, Ming‐Ching, Nils Krahnstoever, Ser-Nam Lim, & Ting Yu. (2010). Group Level Activity Recognition in Crowded Environments across Multiple Cameras. 56–63. 38 indexed citations
20.
Yu, Ting, Ser-Nam Lim, Kedar A. Patwardhan, & Nils Krahnstoever. (2009). Monitoring, recognizing and discovering social networks. 2009 IEEE Conference on Computer Vision and Pattern Recognition. 1462–1469. 60 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

Breakdown of academic impact, for papers by Anthony Hoogs Breakdown of academic impact, for papers by Tom Duerig Breakdown of academic impact, for papers by Shikui Wei Breakdown of academic impact, for papers by Mircea Cimpoi Breakdown of academic impact, for papers by Xiaodong Gu Breakdown of academic impact, for papers by Harish Bhaskar Breakdown of academic impact, for papers by Yongjian Wu Breakdown of academic impact, for papers by Yuan He Breakdown of academic impact, for papers by Brian McWilliams Breakdown of academic impact, for papers by Christopher Olah
Rankless by CCL
2026