World's Best Scientists 2026 revealed!

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Computer Science

D-Index
40
Citations
8489
World Ranking
9178
National Ranking
283

Overview

Anthony Dick is affiliated with the University of Adelaide in Australia and specializes in computer science with a focus on computer vision and pattern recognition as well as artificial intelligence. Their research encompasses key topics such as multimodal machine learning applications, domain adaptation and few-shot learning, topic modeling, and advanced image and video retrieval techniques.

Their recent scholarly output includes publications primarily appearing in the arXiv repository hosted by Cornell University. Notable papers include:

  • Reasoning over Vision and Language: Exploring the Benefits of Supplemental Knowledge, 2021, arXiv (Cornell University)
  • Visual Question Answering with Prior Class Semantics, 2020, arXiv (Cornell University)
  • EBMs vs. CL: Exploring Self-Supervised Visual Pretraining for Visual Question Answering, 2022, arXiv (Cornell University)

Anthony Dick has collaborated frequently with several coauthors, contributing intensively on projects related to their fields of study. Frequent collaborators include:

  • Violetta Shevchenko
  • Damien Teney
  • Anton van den Hengel
  • Ehsan Abbasnejad

Their publications show a pattern of addressing challenges at the intersection of vision and language, leveraging supplemental knowledge to enhance reasoning processes, and exploring self-supervised approaches for visual question answering tasks.

The scientist's work has contributed to advancing understanding in multimodal learning systems, especially those applying knowledge beyond standard visual features to improve interpretability and performance in machine learning tasks.

Best Publications

  • A survey of appearance models in visual object tracking

    Xi Li;Weiming Hu;Chunhua Shen;Zhongfei Zhang

  • What Value Do Explicit High Level Concepts Have in Vision to Language Problems

    Qi Wu;Chunhua Shen;Lingqiao Liu;Anthony Dick

  • Online multi-target tracking using recurrent neural networks

    Anton Milan;S. Hamid Rezatofighi;Anthony Dick;Ian Reid

  • FVQA: Fact-Based Visual Question Answering

    Peng Wang;Qi Wu;Chunhua Shen;Anthony Dick

  • Image Captioning and Visual Question Answering Based on Attributes and External Knowledge

    Qi Wu;Chunhua Shen;Peng Wang;Anthony Dick

  • Visual question answering: A survey of methods and datasets

    Qi Wu;Damien Teney;Peng Wang;Chunhua Shen

  • Ask Me Anything: Free-Form Visual Question Answering Based on Knowledge from External Sources

    Qi Wu;Peng Wang;Chunhua Shen;Anthony Dick

  • Joint Probabilistic Data Association Revisited

    Seyed Hamid Rezatofighi;Anton Milan;Zhen Zhang;Qinfeng Shi

  • VideoTrace: rapid interactive scene modelling from video

    Anton van den Hengel;Anthony Dick;Thorsten Thormählen;Ben Ward

  • Modelling and Interpretation of Architecture from Several Images

    A. R. Dick;P. H. S. Torr;R. Cipolla

  • Contextual Hypergraph Modeling for Salient Object Detection

    Xi Li;Yao Li;Chunhua Shen;Anthony Dick

  • Explicit Knowledge-based Reasoning for Visual Question Answering

    Peng Wang;Qi Wu;Chunhua Shen;Anthony R. Dick

  • Thrift: Local 3D Structure Recognition

    Alex Flint;Anthony Dick;Anton van den Hengel

  • Explicit Knowledge-based Reasoning for Visual Question Answering

    Peng Wang;Qi Wu;Chunhua Shen;Anton van den Hengel

  • Learning Hash Functions Using Column Generation

    Xi Li;Guosheng Lin;Chunhua Shen;Anton Van den Hengel

  • Combining single view recognition and multiple view stereo for architectural scenes

    A.R. Dick;P.H.S. Torr;S.J. Ruffle;R. Cipolla

  • Probabilistic Multiple Cue Integration for Particle Filter Based Tracking

    Chunhua Shen;Anton van den Hengel;Anthony Dick;Mawson Lakes

  • Issues in Automated Visual Surveillance

    Anthony R. Dick;Michael J. Brooks

  • Incremental Learning of 3D-DCT Compact Representations for Robust Visual Tracking

    Xi Li;A. Dick;Chunhua Shen;A. van den Hengel

  • Online Multi-Target Tracking Using Recurrent Neural Networks

    Anton Milan;Seyed Hamid Rezatofighi;Anthony Dick;Ian Reid

  • Image Captioning and Visual Question Answering Based on Attributes and External Knowledge

    Qi Wu;Chunhua Shen;Anton van den Hengel;Peng Wang

Frequent Co-Authors

Anton van den Hengel
Anton van den Hengel University of Adelaide
Chunhua Shen
Chunhua Shen Zhejiang University
Xi Li
Xi Li Zhejiang University
Qi Wu
Qi Wu University of Adelaide
Ian Reid
Ian Reid University of Adelaide
Philip H. S. Torr
Philip H. S. Torr University of Oxford
Qinfeng Shi
Qinfeng Shi University of Adelaide
Roberto Cipolla
Roberto Cipolla University of Cambridge
Zhongfei Zhang
Zhongfei Zhang Binghamton University
Weiming Hu
Weiming Hu Chinese Academy of Sciences

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