World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
37
Citations
10101
World Ranking
10491
National Ranking
4391

Overview

Cuiling Lan is a researcher affiliated with Microsoft in the United States, specializing in computer science with a focus on domain adaptation and computer vision.

Their recent publications include the following:

  • Generalizing to Unseen Domains: A Survey on Domain Generalization, 2022, IEEE Transactions on Knowledge and Data Engineering
  • Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification, 2021, Proceedings of the AAAI Conference on Artificial Intelligence
  • Semantics-Aligned Representation Learning for Person Re-Identification, 2020, Proceedings of the AAAI Conference on Artificial Intelligence
  • ReSTR: Convolution-free Referring Image Segmentation Using Transformers, 2022, 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification, 2020, Proceedings of the AAAI Conference on Artificial Intelligence

Cuiling Lan has collaborated frequently with several co-authors throughout their career. The most frequent co-authors include:

  • Wenjun Zeng
  • Zhibo Chen
  • Zhizheng Zhang
  • Xin Jin
  • Guoqiang Wei

Their publication record spans several key academic venues, with frequent contributions to:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • IEEE Transactions on Multimedia
  • Neurocomputing
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The main fields of study for Cuiling Lan include:

  • Computer Science

Within computer science, their research areas emphasize these subfields:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Biomedical Engineering
  • Radiology, Nuclear Medicine and Imaging
  • Neurology

Their work covers a range of main topics such as:

  • Domain Adaptation and Few-Shot Learning
  • Multimodal Machine Learning Applications
  • Video Surveillance and Tracking Methods
  • Gait Recognition and Analysis
  • Advanced Neural Network Applications
  • Human Pose and Action Recognition
  • Face recognition and analysis

Best Publications

  • An end-to-end spatio-temporal attention model for human action recognition from skeleton data

    Sijie Song;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • Co-occurrence feature learning for skeleton based action recognition using regularized deep LSTM networks

    Wentao Zhu;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • Generalizing to Unseen Domains: A Survey on Domain Generalization

    Jindong Wang;Cuiling Lan;Chang Liu;Yidong Ouyang

  • View Adaptive Recurrent Neural Networks for High Performance Human Action Recognition from Skeleton Data

    Pengfei Zhang;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • Relation-Aware Global Attention for Person Re-Identification

    Zhizheng Zhang;Cuiling Lan;Wenjun Zeng;Xin Jin

  • Semantics-Guided Neural Networks for Efficient Skeleton-Based Human Action Recognition

    Pengfei Zhang;Cuiling Lan;Wenjun Zeng;Junliang Xing

  • View Adaptive Neural Networks for High Performance Skeleton-Based Human Action Recognition

    Pengfei Zhang;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • Style Normalization and Restitution for Generalizable Person Re-Identification

    Xin Jin;Cuiling Lan;Wenjun Zeng;Zhibo Chen

  • Densely Semantically Aligned Person Re-Identification

    Zhizheng Zhang;Cuiling Lan;Wenjun Zeng;Zhibo Chen

  • Generalizing to Unseen Domains: A Survey on Domain Generalization.

    Jindong Wang;Cuiling Lan;Chang Liu;Yidong Ouyang

  • Spatio-Temporal Attention-Based LSTM Networks for 3D Action Recognition and Detection

    Sijie Song;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • Online Human Action Detection Using Joint Classification-Regression Recurrent Neural Networks

    Yanghao Li;Cuiling Lan;Junliang Xing;Wenjun Zeng

  • ReSTR: Convolution-free Referring Image Segmentation Using Transformers

    Unknown

  • Exploiting Sample Uncertainty for Domain Adaptive Person Re-Identification

    Kecheng Zheng;Cuiling Lan;Wenjun Zeng;Zhizheng Zhang

  • Skeleton-Based Action Recognition With Gated Convolutional Neural Networks

    Congqi Cao;Cuiling Lan;Yifan Zhang;Wenjun Zeng

  • Semantics-Aligned Representation Learning for Person Re-Identification

    Xin Jin;Cuiling Lan;Wenjun Zeng;Guoqiang Wei

  • Multi-Granularity Reference-Aided Attentive Feature Aggregation for Video-Based Person Re-Identification

    Zhizheng Zhang;Cuiling Lan;Wenjun Zeng;Zhibo Chen

  • MetaAlign: Coordinating Domain Alignment and Classification for Unsupervised Domain Adaptation

    Guoqiang Wei;Cuiling Lan;Wenjun Zeng;Zhibo Chen

  • EleAtt-RNN: Adding Attentiveness to Neurons in Recurrent Neural Networks

    Pengfei Zhang;Jianru Xue;Cuiling Lan;Wenjun Zeng

  • Uncertainty-Aware Multi-Shot Knowledge Distillation for Image-Based Object Re-Identification

    Xin Jin;Cuiling Lan;Wenjun Zeng;Zhibo Chen

  • Compress Compound Images in H.264/MPGE-4 AVC by Exploiting Spatial Correlation

    Cuiling Lan;Guangming Shi;Feng Wu

  • Adding Attentiveness to the Neurons in Recurrent Neural Networks

    Pengfei Zhang;Jianru Xue;Cuiling Lan;Wenjun Zeng

Frequent Co-Authors

Wenjun Zeng
Wenjun Zeng Microsoft (United States)
Junliang Xing
Junliang Xing Tsinghua University
Feng Wu
Feng Wu University of Science and Technology of China
Xu Jizheng
Xu Jizheng ByteDance
Jiaying Liu
Jiaying Liu Peking University
Guangming Shi
Guangming Shi Xidian University
Shih-Fu Chang
Shih-Fu Chang Columbia University
Jingyu Yang
Jingyu Yang Tianjin University
Zheng-Jun Zha
Zheng-Jun Zha University of Science and Technology of China
Bodo Rosenhahn
Bodo Rosenhahn University of Hannover

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science in the USA opens doors to numerous academic and career options. Many students today seek flexible study options, such as online degrees, to balance education with work or personal commitments. For those aiming to fast-track their education, consider programs like the computer science accelerated program, which allows you to complete your studies in less time while benefiting from a reputable curriculum.

It's also common for students to compare tuition and fees across disciplines. If you're exploring fields beyond computer science, you might find the mechanical engineering degree online cost and the cheapest online environmental science degree worth investigating for budget-friendly alternatives. These comparisons can help guide your decision based on both educational quality and affordability.

Additionally, there is strong demand for tech-savvy professionals across various industries. Consider exploring interdisciplinary roles, such as the diverse jobs for environmental science majors, as they often overlap with computer science and offer unique career pathways. Weighing all your options gives you a broader perspective as you build your future in technology and beyond.

Best Scientists Citing Cuiling Lan

Trending Scientists

Recently Published Articles