Wei Liu
Impact in
- Computer Vision and Pattern Recognition top 0.01%
- Advanced Neural Network Applications
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Video Surveillance and Tracking Methods
- Face recognition and analysis
- Image Enhancement Techniques
- Human Pose and Action Recognition
- Computational Mathematics top 0.2%
Papers in
-
- Advanced Neural Network Applications 48
- Advanced Image and Video Retrieval Techniques 42
- Video Surveillance and Tracking Methods 31
- Multimodal Machine Learning Applications 27
- Face and Expression Recognition 25
- Image Retrieval and Classification Techniques 25
- Generative Adversarial Networks and Image Synthesis 18
-
- Adversarial Robustness in Machine Learning 17
- Co-authors
- Scott Reed (1 shared paper)Dragomir Anguelov (1 shared paper)Christian Szegedy (1 shared paper)Dumitru Erhan (1 shared paper)Shih‐Fu Chang (17 shared papers)Lin Ma (26 shared papers)Yu–Gang Jiang (16 shared papers)Hanwang Zhang (8 shared papers)
- Journals
- IEEE Transactions on Pattern Analysis and Machine Intelligence (24 papers)IEEE Transactions on Image Processing (16 papers)Neurocomputing (10 papers)IEEE Transactions on Circuits and Systems for Video Technology (9 papers)International Journal of Computer Vision (7 papers)
- Partner nations
- ChinaUnited StatesHong Kong
In The Last Decade
Wei Liu
786 papers receiving 63.7k citations
Wei Liu's Hit Papers
Peers
Comparison fields: 5 of 161
- Computer Vision and Pattern Recognition 34.3k
- Computational Mathematics 537
- Media Technology 1.3k
- Artificial Intelligence 5.5k
- Industrial and Manufacturing Engineering 1.4k
Countries citing papers authored by Wei Liu
This map shows the geographic impact of Wei Liu'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 Wei Liu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Wei Liu more than expected).
Fields of papers citing papers by Wei Liu
This network shows the impact of papers produced by Wei Liu. 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 Wei Liu. The network helps show where Wei Liu may publish in the future.
Co-authors
The 25 scholars most cited alongside Wei Liu, 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 840 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | SSD: Single Shot MultiBox Detector Hit paper breakdown → | 2016 | 24140 |
| 2 | CosFace: Large Margin Cosine Loss for Deep Face Recognition Hit paper breakdown → | 2018 | 2139 |
| 3 | Frustum PointNets for 3D Object Detection from RGB-D Data Hit paper breakdown → | 2018 | 2031 |
| 4 | SCA-CNN: Spatial and Channel-Wise Attention in Convolutional Networks for Image Captioning Hit paper breakdown → | 2017 | 1618 |
| 5 | Supervised hashing with kernels Hit paper breakdown → | 2012 | 1128 |
| 6 | Enhancing Geometric Factors in Model Learning and Inference for Object Detection and Instance Segmentation Hit paper breakdown → | 2021 | 1113 |
| 7 | Supervised Discrete Hashing Hit paper breakdown → | 2015 | 1017 |
| 8 | Pixel2Mesh: Generating 3D Mesh Models from Single RGB Images Hit paper breakdown → | 2018 | 964 |
| 9 | Tensor Robust Principal Component Analysis with a New Tensor Nuclear Norm Hit paper breakdown → | 2019 | 846 |
| 10 | Gated Fusion Network for Single Image Dehazing Hit paper breakdown → | 2018 | 791 |
| 11 | Beyond Brightening Low-light Images Hit paper breakdown → | 2021 | 687 |
| 12 | Attentive Collaborative Filtering Hit paper breakdown → | 2017 | 686 |
| 13 | Multiple object tracking: A literature review Hit paper breakdown → | 2020 | 682 |
| 14 | Tensor Robust Principal Component Analysis: Exact Recovery of Corrupted Low-Rank Tensors via Convex Optimization Hit paper breakdown → | 2016 | 440 |
| 15 | 2018 | 424 | |
| 16 | 2019 | 410 | |
| 17 | Generalizing Face Forgery Detection with High-frequency Features Hit paper breakdown → | 2021 | 401 |
| 18 | Learning to Hash for Indexing Big Data—A Survey Hit paper breakdown → | 2015 | 399 |
| 19 | 2018 | 393 | |
| 20 | Large Graph Construction for Scalable Semi-Supervised Learning Hit paper breakdown → | 2010 | 392 |
About Wei Liu
Wei Liu is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Media Technology, Computational Mechanics and Signal Processing, having authored 840 papers that have together received 65.4k indexed citations. Recurring topics across this work include Advanced Neural Network Applications (48 papers), Advanced Image and Video Retrieval Techniques (42 papers), Video Surveillance and Tracking Methods (31 papers), Multimodal Machine Learning Applications (27 papers), Face and Expression Recognition (25 papers), Image Retrieval and Classification Techniques (25 papers), Generative Adversarial Networks and Image Synthesis (18 papers) and Adversarial Robustness in Machine Learning (17 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (34.3k citations), Computational Mathematics (537 citations), Media Technology (1.3k citations), Artificial Intelligence (5.5k citations) and Industrial and Manufacturing Engineering (1.4k citations). Wei Liu has collaborated with scholars based in China, United States and Hong Kong. Frequent co-authors include Scott Reed, Dragomir Anguelov, Christian Szegedy, Dumitru Erhan, Shih‐Fu Chang, Lin Ma, Yu–Gang Jiang, Hanwang Zhang, Wenhan Luo and Dacheng Tao. Their work appears in journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, IEEE Transactions on Image Processing, Neurocomputing, IEEE Transactions on Circuits and Systems for Video Technology and International Journal of Computer Vision.
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.