World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
8722
World Ranking
7172
National Ranking
228

Overview

Nick Barnes is affiliated with the Australian National University in Australia and has contributed extensively to the field of computer science, with a particular focus on computer vision and artificial intelligence. Their research spans a variety of specialized topics, demonstrating a multidisciplinary approach within the areas of visual attention, neural networks, and 3D data processing.

Their recent published works include:

  • A Deep Journey into Super-resolution, 2020, ACM Computing Surveys
  • A Comprehensive Overview of Large Language Models, 2023, arXiv (Cornell University)
  • Geometric Back-Projection Network for Point Cloud Classification, 2021, IEEE Transactions on Multimedia
  • A Comprehensive Overview of Large Language Models, 2025, ACM Transactions on Intelligent Systems and Technology
  • Uncertainty Inspired RGB-D Saliency Detection, 2021, IEEE Transactions on Pattern Analysis and Machine Intelligence

Nick Barnes frequently collaborates with a number of researchers, including:

  • Saeed Anwar
  • Jing Zhang
  • Yuchao Dai
  • Shi Qiu

Their work has appeared in several notable venues, among which the most frequent are:

  • arXiv (Cornell University)
  • IEEE Transactions on Pattern Analysis and Machine Intelligence
  • Translational Vision Science & Technology
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)

Within computer science, Nick Barnes focuses on the subfields of:

  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Cognitive Neuroscience
  • Computational Mechanics
  • Radiology, Nuclear Medicine and Imaging

Their research covers a range of topics, including:

  • Visual Attention and Saliency Detection
  • Advanced Neural Network Applications
  • Domain Adaptation and Few-Shot Learning
  • Advanced Image and Video Retrieval Techniques
  • 3D Shape Modeling and Analysis
  • Multimodal Machine Learning Applications
  • 3D Surveying and Cultural Heritage

Best Publications

  • Real Image Denoising With Feature Attention

    Saeed Anwar;Nick Barnes

  • Simultaneously Localize, Segment and Rank the Camouflaged Objects

    Yunqiu Lv;Jing Zhang;Yuchao Dai;Aixuan Li

  • Fast shape-based road sign detection for a driver assistance system

    G. Loy;N. Barnes

  • A Deep Journey into Super-resolution: A Survey

    Saeed Anwar;Salman Khan;Nick Barnes

  • UC-Net: Uncertainty Inspired RGB-D Saliency Detection via Conditional Variational Autoencoders

    Jing Zhang;Deng-Ping Fan;Yuchao Dai;Saeed Anwar

  • A Comprehensive Overview of Large Language Models

    Unknown

  • First-in-Human Trial of a Novel Suprachoroidal Retinal Prosthesis

    Lauren N Ayton;Peter J. Blamey;Robyn H. Guymer;Chi D Luu

  • Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion

    Shi Qiu;Saeed Anwar;Nick Barnes

  • Geometric Back-projection Network for Point Cloud Classification

    Shi Qiu;Saeed Anwar;Nick Barnes

  • A Comprehensive Overview of Large Language Models

    Unknown

  • Real-time radial symmetry for speed sign detection

    N. Barnes;A. Zelinsky

  • Real-Time Speed Sign Detection Using the Radial Symmetry Detector

    N. Barnes;A. Zelinsky;L.S. Fletcher

  • Local Background Enclosure for RGB-D Salient Object Detection

    David Feng;Nick Barnes;Shaodi You;Chris McCarthy

  • Densely Residual Laplacian Super-Resolution.

    Saeed Anwar;Nick Barnes

  • Fast Image Reconstruction with an Event Camera

    Cedric Scheerlinck;Henri Rebecq;Daniel Gehrig;Nick Barnes

  • Continuous-Time Intensity Estimation Using Event Cameras

    Cedric Scheerlinck;Nick Barnes;Robert E. Mahony

  • Correlating driver gaze with the road scene for driver assistance systems

    Luke Fletcher;Gareth Loy;Nick Barnes;Alexander Zelinsky

  • Uncertainty Inspired RGB-D Saliency Detection.

    Jing Zhang;Deng-Ping Fan;Yuchao Dai;Saeed Anwar

  • RGB-D Saliency Detection via Cascaded Mutual Information Minimization

    Jing Zhang;Deng-Ping Fan;Yuchao Dai;Xin Yu

  • Dense-Resolution Network for Point Cloud Classification and Segmentation

    Shi Qiu;Saeed Anwar;Nick Barnes

  • Reducing the Sim-to-Real Gap for Event Cameras

    Timo Stoffregen;Cedric Scheerlinck;Davide Scaramuzza;Tom Drummond

  • Improved Visual-Semantic Alignment for Zero-Shot Object Detection

    Shafin Rahman;Salman H. Khan;Nick Barnes

  • Speeding up Mutual Information Computation Using NVIDIA CUDA Hardware

    Ramtin Shams;Nick Barnes

  • The regular polygon detector

    Nick Barnes;Gareth Loy;David Shaw

Frequent Co-Authors

Xuming He
Xuming He Washington University in St. Louis
Alexander Zelinsky
Alexander Zelinsky University of Newcastle Australia
Yuchao Dai
Yuchao Dai Northwestern Polytechnical University
Stephen Gould
Stephen Gould Australian National University
Robert Mahony
Robert Mahony Australian National University
Richard Hartley
Richard Hartley Australian National University
Chunhua Shen
Chunhua Shen Zhejiang University
Elinor McKone
Elinor McKone Australian National University
Mathieu Salzmann
Mathieu Salzmann École Polytechnique Fédérale de Lausanne
Lars Petersson
Lars Petersson Commonwealth Scientific and Industrial Research Organisation

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

The field of Computer Science offers several flexible education options to support your career goals. From foundational programs to advanced degrees, online learning opens doors for students with diverse academic backgrounds and needs.

For those starting out, online associate degree programs in Computer Science provide a solid entry point and can lead to roles such as IT support or junior developers. If you’re concerned about the cost of education, exploring the cheapest online college options can make earning a degree more accessible.

Aspiring professionals with a passion for advancement might consider the most useful masters degrees in tech. These programs often lead to specialized, high-demand career paths like data science or cybersecurity. Additionally, if academic performance is a concern, don’t let it hold you back—several college that accepts low gpa are available, giving more students the chance to succeed in this dynamic field.

Best Scientists Citing Nick Barnes

Trending Scientists

Recently Published Articles