Li Fei-Fei
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Neural Network Applications
- Multimodal Machine Learning Applications
- Human Pose and Action Recognition
- Advanced Image and Video Retrieval Techniques
- Generative Adversarial Networks and Image Synthesis
- Image Retrieval and Classification Techniques
- Video Surveillance and Tracking Methods
- Artificial Intelligence top 0.01%
- Domain Adaptation and Few-Shot Learning
Papers in
-
- Advanced Neural Network Applications 56
- Advanced Image and Video Retrieval Techniques 52
- Human Pose and Action Recognition 46
- Multimodal Machine Learning Applications 42
-
- Reinforcement Learning in Robotics 36
- Domain Adaptation and Few-Shot Learning 31
- Co-authors
- Jia Hao Deng (26 shared papers)Li-Jia Li (28 shared papers)Richard Socher (5 shared papers)Kai Li (3 shared papers)Wei Dong (1 shared paper)Andrej Karpathy (8 shared papers)Justin M. Johnson (13 shared papers)Alexandre Alahi (17 shared papers)
- Journals
- Journal of Vision (18 papers)International Journal of Computer Vision (6 papers)IEEE Transactions on Pattern Analysis and Machine Intelligence (5 papers)npj Digital Medicine (4 papers)NeuroImage (4 papers)
- Partner nations
- United StatesUnited KingdomChina
In The Last Decade
Li Fei-Fei
327 papers receiving 148.6k citations
Li Fei-Fei's Hit Papers
Peers
Comparison fields: 5 of 223
- Computer Vision and Pattern Recognition 91.2k
- Artificial Intelligence 36k
- Health Informatics 1.4k
- Automotive Engineering 4.6k
- Media Technology 3.5k
Countries citing papers authored by Li Fei-Fei
This map shows the geographic impact of Li Fei-Fei'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 Li Fei-Fei with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Li Fei-Fei more than expected).
Fields of papers citing papers by Li Fei-Fei
This network shows the impact of papers produced by Li Fei-Fei. 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 Li Fei-Fei. The network helps show where Li Fei-Fei may publish in the future.
Co-authors
The 25 scholars most cited alongside Li Fei-Fei, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 339 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | ImageNet: A large-scale hierarchical image database Hit paper breakdown → | 2009 | 44545 |
| 2 | ImageNet Large Scale Visual Recognition Challenge Hit paper breakdown → | 2015 | 29121 |
| 3 | Perceptual Losses for Real-Time Style Transfer and Super-Resolution Hit paper breakdown → | 2016 | 7951 |
| 4 | Large-Scale Video Classification with Convolutional Neural Networks Hit paper breakdown → | 2014 | 5078 |
| 5 | Visual Genome: Connecting Language and Vision Using Crowdsourced Dense Image Annotations Hit paper breakdown → | 2017 | 3814 |
| 6 | Deep visual-semantic alignments for generating image descriptions Hit paper breakdown → | 2015 | 3514 |
| 7 | A Bayesian Hierarchical Model for Learning Natural Scene Categories Hit paper breakdown → | 2005 | 2873 |
| 8 | Social LSTM: Human Trajectory Prediction in Crowded Spaces Hit paper breakdown → | 2016 | 2600 |
| 9 | 3D Object Representations for Fine-Grained Categorization Hit paper breakdown → | 2013 | 2490 |
| 10 | One-shot learning of object categories Hit paper breakdown → | 2006 | 2230 |
| 11 | ImageNet: A large-scale hierarchical image database Hit paper breakdown → | 2009 | 2017 |
| 12 | Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks Hit paper breakdown → | 2018 | 1758 |
| 13 | Learning generative visual models from few training examples: An incremental Bayesian approach tested on 101 object categories Hit paper breakdown → | 2007 | 1713 |
| 14 | Progressive Neural Architecture Search Hit paper breakdown → | 2018 | 1280 |
| 15 | Unsupervised Learning of Human Action Categories Using Spatial-Temporal Words Hit paper breakdown → | 2008 | 1200 |
| 16 | CLEVR: A Diagnostic Dataset for Compositional Language and Elementary Visual Reasoning Hit paper breakdown → | 2017 | 1145 |
| 17 | Target-driven visual navigation in indoor scenes using deep reinforcement learning Hit paper breakdown → | 2017 | 1117 |
| 18 | Dense-Captioning Events in Videos Hit paper breakdown → | 2017 | 934 |
| 19 | Scene Graph Generation by Iterative Message Passing Hit paper breakdown → | 2017 | 920 |
| 20 | DenseCap: Fully Convolutional Localization Networks for Dense Captioning Hit paper breakdown → | 2016 | 866 |
About Li Fei-Fei
Li Fei-Fei is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Control and Systems Engineering and Computer Science Applications, having authored 339 papers that have together received 152.7k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (56 papers), Advanced Image and Video Retrieval Techniques (52 papers), Human Pose and Action Recognition (46 papers), Multimodal Machine Learning Applications (42 papers), Reinforcement Learning in Robotics (36 papers), Visual perception and processing mechanisms (31 papers), Domain Adaptation and Few-Shot Learning (31 papers) and Robot Manipulation and Learning (31 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (91.2k citations), Artificial Intelligence (36k citations), Health Informatics (1.4k citations), Automotive Engineering (4.6k citations) and Media Technology (3.5k citations). Li Fei-Fei has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Jia Hao Deng, Li-Jia Li, Richard Socher, Kai Li, Wei Dong, Andrej Karpathy, Justin M. Johnson, Alexandre Alahi, Jonathan Krause and Michael S. Bernstein. Their work appears in journals such as Journal of Vision, International Journal of Computer Vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, npj Digital Medicine and NeuroImage.
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.