Tom Duerig

5.0k total citations · 2 hit papers
6 papers, 1.5k citations indexed

About

Tom Duerig is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Tom Duerig has authored 6 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Computer Vision and Pattern Recognition, 3 papers in Artificial Intelligence and 0 papers in Infectious Diseases. Recurrent topics in Tom Duerig's work include Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Tom Duerig is often cited by papers focused on Multimodal Machine Learning Applications (6 papers), Advanced Neural Network Applications (5 papers) and Advanced Image and Video Retrieval Techniques (4 papers). Tom Duerig collaborates with scholars based in United States and Switzerland. Tom Duerig's co-authors include Neil Alldrin, Alina Kuznetsova, Jasper Uijlings, Shahab Kamali, Jordi Pont-Tuset, Ivan Krasin, Stefan Popov, Alexander Kolesnikov, Vittorio Ferrari and Zhen Li and has published in prestigious journals such as International Journal of Computer Vision, arXiv (Cornell University) and International Conference on Machine Learning.

In The Last Decade

Tom Duerig

6 papers receiving 1.4k 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.

The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

2018 960 citations Alina Kuznetsova, Neil Alldrin et al. arXiv (Cornell University) profile →
The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale

2018 378 citations Alina Kuznetsova, Neil Alldrin et al. arXiv (Cornell University) profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tom Duerig United States	6	1.1k	631	87	87	76	6	1.5k
Alina Kuznetsova United States	9	1.3k 1.2×	713 1.1×	88 1.0×	89 1.0×	91 1.2×	12	1.8k
Ivan Krasin United States	5	1.2k 1.1×	808 1.3×	98 1.1×	91 1.0×	85 1.1×	5	1.8k
Shahab Kamali United States	8	1.1k 1.0×	652 1.0×	87 1.0×	83 1.0×	83 1.1×	13	1.6k
Neil Alldrin United States	9	1.5k 1.4×	815 1.3×	102 1.2×	93 1.1×	89 1.2×	11	2.1k
Stefan Popov United States	12	1.4k 1.3×	645 1.0×	103 1.2×	95 1.1×	109 1.4×	15	2.0k
Lucas Beyer Germany	11	932 0.9×	775 1.2×	85 1.0×	112 1.3×	60 0.8×	15	1.6k
Keze Wang China	16	874 0.8×	543 0.9×	110 1.3×	75 0.9×	42 0.6×	38	1.3k
Robinson Piramuthu United States	12	907 0.8×	424 0.7×	115 1.3×	86 1.0×	28 0.4×	26	1.3k
Zunlei Feng China	14	762 0.7×	281 0.4×	84 1.0×	65 0.7×	98 1.3×	83	1.3k
Ronghang Hu United States	13	1.5k 1.4×	1.1k 1.8×	106 1.2×	105 1.2×	72 0.9×	17	2.2k

Countries citing papers authored by Tom Duerig

Since Specialization

Citations

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

Fields of papers citing papers by Tom Duerig

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tom Duerig

This figure shows the co-authorship network connecting the top 25 collaborators of Tom Duerig. A scholar is included among the top collaborators of Tom Duerig 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 Tom Duerig. Tom Duerig 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:

6 of 6 papers shown

1.

Alldrin, Neil, Otilia Stretcu, Hao Xiong, et al.. (2024). Modeling Collaborator: Enabling Subjective Vision Classification with Minimal Human Effort via LLM Tool-Use. 17553–17563. 5 indexed citations

2.

Jia, Chao, Yinfei Yang, Ye Xia, et al.. (2021). Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision. International Conference on Machine Learning. 4904–4916. 5 indexed citations

3.

Kuznetsova, Alina, Neil Alldrin, Jasper Uijlings, et al.. (2020). The Open Images Dataset V4. International Journal of Computer Vision. 128(7). 1956–1981. 130 indexed citations

4.

Juan, Da-Cheng, Chun-Ta Lu, Zhen Li, et al.. (2020). Ultra Fine-Grained Image Semantic Embedding. 277–285. 12 indexed citations

5.

Kuznetsova, Alina, Neil Alldrin, Jasper Uijlings, et al.. (2018). The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale. arXiv (Cornell University). 960 indexed citations breakdown →

6.

Kuznetsova, Alina, Neil Alldrin, Jasper Uijlings, et al.. (2018). The Open Images Dataset V4: Unified image classification, object detection, and visual relationship detection at scale. arXiv (Cornell University). 128(7). 1956–1981. 378 indexed citations breakdown →

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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