Haoqi Fan

23.1k citations
30 papers · 11.4k · 6 hit papers · h-index 19

Impact in

    • Human Pose and Action Recognition
    • Multimodal Machine Learning Applications
    • Advanced Neural Network Applications
    • Advanced Image and Video Retrieval Techniques
    • Video Surveillance and Tracking Methods
    • Domain Adaptation and Few-Shot Learning
    • Anomaly Detection Techniques and Applications
    • Topic Modeling

Papers in

    • Multimodal Machine Learning Applications 13
    • Human Pose and Action Recognition 12
    • Advanced Neural Network Applications 11
    • Advanced Image and Video Retrieval Techniques 4
    • Video Surveillance and Tracking Methods 3
    • Domain Adaptation and Few-Shot Learning 12
    • Anomaly Detection Techniques and Applications 4
    • Adversarial Robustness in Machine Learning 2
Journals
Flow Measurement and Instrumentation (1 paper)Journal of Low Temperature Physics (1 paper)2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) (6 papers)2021 IEEE/CVF International Conference on Computer Vision (ICCV) (3 papers)arXiv (Cornell University) (1 paper)
Partner nations
United StatesIsraelChina

In The Last Decade

Haoqi Fan

28 papers receiving 11.1k citations

Hit Papers

Scaling Language-Image Pre-Training via Masking 2023 · 112 citations
1120+2+4Years since publication2.0k4.0k6.0k

Peers

Haoqi Fan
Comparison fields: 5 of 176
  • Computer Vision and Pattern Recognition 7.3k
  • Artificial Intelligence 6.0k
  • Media Technology 784
  • Human-Computer Interaction 417
  • Signal Processing 576
Replace Sergio Guadarrama with:
Sergio Guadarrama United States
Honglak Lee United States
Liang Lin China
Kate Saenko United States
Jun Yu China
Raia Hadsell United States
Mingkui Tan China
Christoph Feichtenhofer United States
Bingbing Ni China
Weiming Hu China
Haoqi Fan relative to Sergio Guadarrama United States Sergio Guadarrama's profile →
Citations per field
00.5×8.5×
Sergio Guadarrama · 1×
Citations per year

Countries citing papers authored by Haoqi Fan

Since Specialization
Citations

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

Fields of papers citing papers by Haoqi Fan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Haoqi Fan, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Haoqi Fan Line = papers co-authored together Haoqi Fan links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Momentum Contrast for Unsupervised Visual Representation Learning
Hit paper breakdown →
20206956
2
SlowFast Networks for Video Recognition
Hit paper breakdown →
20192000
3
Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks With Octave Convolution
Hit paper breakdown →
2019439
4
MViTv2: Improved Multiscale Vision Transformers for Classification and Detection
Hit paper breakdown →
2022424
5
Masked Feature Prediction for Self-Supervised Visual Pre-Training
Hit paper breakdown →
2022324
6 2019242
7 2016161
8 2021136
9
Scaling Language-Image Pre-Training via Masking
Hit paper breakdown →
2023112
10 2021107
11 202294
12 202289
13 202139
14 201834
15 202229
16 202128
17 202326
18 202223
19 201821
20 202418

About Haoqi Fan

Haoqi Fan is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Electrical and Electronic Engineering, Aerospace Engineering and Mechanical Engineering, having authored 30 papers that have together received 11.4k indexed citations. Recurring topics across this work include Multimodal Machine Learning Applications (13 papers), Human Pose and Action Recognition (12 papers), Domain Adaptation and Few-Shot Learning (12 papers), Advanced Neural Network Applications (11 papers), Advanced Image and Video Retrieval Techniques (4 papers), Anomaly Detection Techniques and Applications (4 papers), Video Surveillance and Tracking Methods (3 papers) and Adversarial Robustness in Machine Learning (2 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (7.3k citations), Artificial Intelligence (6.0k citations), Media Technology (784 citations), Human-Computer Interaction (417 citations) and Signal Processing (576 citations). Haoqi Fan has collaborated with scholars based in United States, Israel and China. Frequent co-authors include Kaiming He, Ross Girshick, Saining Xie, Yuxin Wu, Christoph Feichtenhofer, Jitendra Malik, Chao-Yuan Wu, Bo Xiong, Yanghao Li and Karttikeya Mangalam. Their work appears in journals such as Flow Measurement and Instrumentation, Journal of Low Temperature Physics, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2021 IEEE/CVF International Conference on Computer Vision (ICCV) and arXiv (Cornell University).

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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