Matt Feiszli

64 total papers · 2.1k total citations
20 papers, 925 citations indexed

About

Matt Feiszli is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Computational Mechanics. According to data from OpenAlex, Matt Feiszli has authored 20 papers receiving a total of 925 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Computer Vision and Pattern Recognition, 10 papers in Artificial Intelligence and 2 papers in Computational Mechanics. Recurrent topics in Matt Feiszli's work include Human Pose and Action Recognition (9 papers), Multimodal Machine Learning Applications (8 papers) and Anomaly Detection Techniques and Applications (7 papers). Matt Feiszli is often cited by papers focused on Human Pose and Action Recognition (9 papers), Multimodal Machine Learning Applications (8 papers) and Anomaly Detection Techniques and Applications (7 papers). Matt Feiszli collaborates with scholars based in United States, Israel and Singapore. Matt Feiszli's co-authors include Du Tran, Wei‐Yao Wang, Heng Wang, Lorenzo Torresani, Heng Wang, Deepti Ghadiyaram, Stan Weixian Lei, Mike Zheng Shou, Jitendra Malik and Heng Wang and has published in prestigious journals such as Applied and Computational Harmonic Analysis, 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

In The Last Decade

Matt Feiszli

19 papers receiving 897 citations

Hit Papers

Video Classification With... 2019 2026 2021 2023 2019 2020 100 200 300
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 benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. Video Classification With Channel-Separated Convolutional Networks
    2019 371 citations Du Tran, Heng Wang et al. profile →
  2. What Makes Training Multi-Modal Classification Networks Hard?
    2020 289 citations Wei‐Yao Wang, Du Tran et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Matt Feiszli 690 456 89 85 57 20 925
Rohit Girdhar 766 1.1× 371 0.8× 70 0.8× 77 0.9× 46 0.8× 19 1.1k
Xi Peng 593 0.9× 303 0.7× 111 1.2× 118 1.4× 88 1.5× 41 968
L. Zhao 568 0.8× 359 0.8× 71 0.8× 57 0.7× 59 1.0× 41 973
Bo Xiong 966 1.4× 405 0.9× 78 0.9× 75 0.9× 64 1.1× 23 1.2k
Yandong Li 442 0.6× 428 0.9× 97 1.1× 128 1.5× 63 1.1× 33 1.0k
Avinash Ravichandran 825 1.2× 454 1.0× 118 1.3× 107 1.3× 62 1.1× 18 1.1k
Karttikeya Mangalam 574 0.8× 331 0.7× 50 0.6× 48 0.6× 35 0.6× 17 851
Zhenzhong Lan 787 1.1× 549 1.2× 129 1.4× 81 1.0× 59 1.0× 49 1.1k
Ashish Jaiswal 404 0.6× 521 1.1× 66 0.7× 76 0.9× 119 2.1× 17 1.2k
Zhe Wang 952 1.4× 437 1.0× 184 2.1× 41 0.5× 112 2.0× 26 1.1k

Countries citing papers authored by Matt Feiszli

Since Specialization
Citations

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

Fields of papers citing papers by Matt Feiszli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matt Feiszli

This figure shows the co-authorship network connecting the top 25 collaborators of Matt Feiszli. A scholar is included among the top collaborators of Matt Feiszli 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 Matt Feiszli. Matt Feiszli is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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2026