World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
38
Citations
9491
World Ranking
10010
National Ranking
1253

Overview

Lai-Man Po is affiliated with the City University of Hong Kong in China and has made significant contributions primarily in the field of Computer Science. The research output reflects a strong focus on Computer Vision and Pattern Recognition, which accounts for the majority of their publications. Other notable subfields include Artificial Intelligence, Signal Processing, Media Technology, and Genetics.

The scientist's research topics cover a variety of advanced areas within image and signal processing as well as machine learning techniques. Key topics of their work include:

  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Generative Adversarial Networks and Image Synthesis
  • Advanced Image Processing Techniques
  • Image and Signal Denoising Methods
  • Advanced Vision and Imaging
  • Advanced Image Fusion Techniques

Lai-Man Po has published extensively in several scientific venues, with a significant number of papers appearing in:

  • arXiv (Cornell University)
  • Expert Systems with Applications
  • SSRN Electronic Journal
  • IEEE Transactions on Multimedia
  • Sensors

Their recent published works demonstrate engagement with topics like large kernel attention mechanisms in convolutional neural networks, GAN-based colorization techniques, and feature learning for biometric recognition. Some notable recent papers include:

  • Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in Cnn, 2023, SSRN Electronic Journal
  • Large Separable Kernel Attention: Rethinking the Large Kernel Attention design in CNN, 2023, Expert Systems with Applications
  • VCGAN: Video Colorization With Hybrid Generative Adversarial Network, 2022, IEEE Transactions on Multimedia
  • SCGAN: Saliency Map-Guided Colorization With Generative Adversarial Network, 2020, IEEE Transactions on Circuits and Systems for Video Technology
  • Fusion loss and inter-class data augmentation for deep finger vein feature learning, 2021, Expert Systems with Applications

The scientist collaborates regularly with several researchers in their field. Frequent coauthors include:

  • Yuzhi Zhao
  • Wing-Yin Yu
  • Yasar Abbas Ur Rehman
  • Weifeng Ou
  • Kin Wai Lau

Lai-Man Po's body of work contributes to developments in neural networks and generative adversarial network applications, especially within advanced image and video processing tasks. Their research intersects with cutting-edge approaches to image synthesis, domain adaptation, and feature learning, reflecting a multidisciplinary approach within computer science and engineering domains.

Best Publications

  • A novel four-step search algorithm for fast block motion estimation

    Lai-Man Po;Wing-Chung Ma

  • A novel cross-diamond search algorithm for fast block motion estimation

    Chun-Ho Cheung;Lai-Man Po

  • A novel rood-diamond search algorithm for fast block motion estimation

    Chun-Ho Cheung;Lai-Man Po

  • Large Separable Kernel Attention: Rethinking the Large Kernel Attention Design in CNN

    Unknown

  • Integration of image quality and motion cues for face anti-spoofing

    Litong Feng;Lai-Man Po;Yuming Li;Xuyuan Xu

  • Novel cross-diamond-hexagonal search algorithms for fast block motion estimation

    Chun-Ho Cheung;Lai-Man Po

  • Normalized partial distortion search algorithm for block motion estimation

    Chok-Kwan Cheung;Lai-Man Po

  • Enhanced hexagonal search for fast block motion estimation

    Ce Zhu;Xiao Lin;L. Chau;Lai-Man Po

  • Edge-Based Structural Similarity for Image Quality Assessment

    Guan-Hao Chen;Chun-Ling Yang;Lai-Man Po;Sheng-Li Xie

  • Motion-Resistant Remote Imaging Photoplethysmography Based on the Optical Properties of Skin

    Litong Feng;Lai-Man Po;Xuyuan Xu;Yuming Li

  • Hierarchical Regression Network for Spectral Reconstruction from RGB Images

    Yuzhi Zhao;Lai-Man Po;Qiong Yan;Wei Liu

  • Adaptive motion tracking block matching algorithms for video coding

    Jie-Bin Xu;Lai-Man Po;Chok-Kwan Cheung

  • Cuffless Blood Pressure Estimation Based on Photoplethysmography Signal and Its Second Derivative

    Mengyang Liu;Lai-Man Po;Hong Fu

  • No-Reference Video Quality Assessment With 3D Shearlet Transform and Convolutional Neural Networks

    Yuming Li;Lai-Man Po;Chun-Ho Cheung;Xuyuan Xu

  • Adjustable partial distortion search algorithm for fast block motion estimation

    Chun-Ho Cheung;Lai-Man Po

  • A fast H.264 intra prediction algorithm using macroblock properties

    Chun-Ling Yang;Lai-Man Po;Wing-Hong Lam

  • LiveNet: Improving features generalization for face liveness detection using convolution neural networks

    Yasar Abbas Ur Rehman;Lai Man Po;Mengyang Liu

  • MIRROR: an interactive content based image retrieval system

    Ka-Man Wong;Kwok-Wai Cheung;Lai-Man Po

  • No-reference image quality assessment with shearlet transform and deep neural networks

    Yuming Li;Lai-Man Po;Xuyuan Xu;Litong Feng

  • A novel kite-cross-diamond search algorithm for fast block matching motion estimation

    Chi-Wai Lam;Lai-Man Po;Chun Ho Cheung

  • Novel Directional Gradient Descent Searches for Fast Block Motion Estimation

    Lai-Man Po;Ka-Ho Ng;Kwok-Wai Cheung;Ka-Man Wong

Frequent Co-Authors

Ce Zhu
Ce Zhu University of Electronic Science and Technology of China
Q. M. Jonathan Wu
Q. M. Jonathan Wu University of Windsor
Yuan-Ting Zhang
Yuan-Ting Zhang City University of Hong Kong
Shengli Xie
Shengli Xie Guangdong University of Technology
Radu Timofte
Radu Timofte University of Wurzburg
Jechang Jeong
Jechang Jeong Hanyang University
Lap-Pui Chau
Lap-Pui Chau Hong Kong Polytechnic University
Sung-Jea Ko
Sung-Jea Ko Korea University

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

Expanding your education in computer science opens doors to diverse career pathways, both within and beyond the field. Many students seek flexible options, such as online programs, which can offer greater accessibility and affordability. If you’re concerned about cost, exploring the cheapest bachelor’s degree online can help you find top-value programs without sacrificing quality.

Those interested in technical or STEM-oriented roles might consider pursuing an online bachelor’s in engineering. This pathway aligns well with many computer science foundations and can prepare you for a range of in-demand engineering careers.

For professionals aiming to move into leadership or managerial roles, continuing on to an affordable EMBA program can provide crucial business and management skills to complement your technical expertise.

Additionally, if you are drawn to information management or positions in academic, public, or special libraries, you might explore the cheapest MLIS degree online. This can open new opportunities in data curation and digital information careers.

Best Scientists Citing Lai-Man Po

Trending Scientists

Recently Published Articles