World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
44
Citations
6616
World Ranking
7677
National Ranking
243

Overview

Tat-Jun Chin is affiliated with the University of Adelaide in Australia. Their research output spans multiple fields within computer science and engineering, with a focus on aerospace engineering, computer vision and pattern recognition, and artificial intelligence.

The scientist's publication record includes significant contributions across various subfields and topics. Key subfields of study are:

  • Aerospace Engineering
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence
  • Astronomy and Astrophysics
  • Electrical and Electronic Engineering

Main topics of research covered in their work include:

  • Robotics and Sensor-Based Localization
  • Space Satellite Systems and Control
  • Advanced Image and Video Retrieval Techniques
  • Planetary Science and Exploration
  • Advanced Neural Network Applications
  • Inertial Sensor and Navigation
  • Machine Learning and Algorithms

Among more recent papers, notable titles include:

  • "Semantics for Robotic Mapping, Perception and Interaction: A Survey" (2020), published in Foundations and Trends in Robotics
  • "Physical Adversarial Attacks on an Aerial Imagery Object Detector" (2022), presented at the 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • "Auto-Rectify Network for Unsupervised Indoor Depth Estimation" (2021), published in IEEE Transactions on Pattern Analysis and Machine Intelligence
  • "Satellite Pose Estimation Competition 2021: Results and Analyses" (2023), published in Acta Astronautica
  • "Topological Sweep for Multi-Target Detection of Geostationary Space Objects" (2020), published in IEEE Transactions on Signal Processing

Frequent coauthors in Tat-Jun Chin's collaborations include:

  • Ian Reid
  • Anh-Dzung Doan
  • Yasir Latif
  • Michele Sasdelli
  • Daqi Liu

Publication venues with multiple contributions from Tat-Jun Chin highlight activity in both conference and journal formats, including:

  • arXiv (Cornell University)
  • Zenodo (CERN European Organization for Nuclear Research)
  • Acta Astronautica
  • 2022 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

The scientist has also contributed to book publications with Springer Science+Business Media, notably as part of the volume "Computer Vision - ACCV 2022" published in 2023.

Tat-Jun Chin's work primarily intersects the disciplines of computer science and engineering, with substantial research focused on applications involving robotics, satellite systems, and advanced imaging methodologies.

Best Publications

  • As-Projective-As-Possible Image Stitching with Moving DLT

    Unknown

  • As-Projective-As-Possible Image Stitching with Moving DLT

    Julio Zaragoza;Tat-Jun Chin;Quoc-Huy Tran;Michael S. Brown

  • Incremental Kernel Principal Component Analysis

    Tat-Jun Chin;D. Suter

  • Guaranteed Outlier Removal for Point Cloud Registration with Correspondences

    Alvaro Parra Bustos;Tat-Jun Chin

  • Dynamic and hierarchical multi-structure geometric model fitting

    Hoi Sim Wong;Tat-Jun Chin;Jin Yu;David Suter

  • Semantics for Robotic Mapping, Perception and Interaction: A Survey

    Sourav Garg;Niko Sünderhauf;Feras Dayoub;Douglas Morrison

  • Simultaneously Fitting and Segmenting Multiple-Structure Data with Outliers

    Hanzi Wang;Tat-Jun Chin;D. Suter

  • Satellite Pose Estimation with Deep Landmark Regression and Nonlinear Pose Refinement

    Bo Chen;Jiewei Cao;Alvaro Parra;Tat-Jun Chin

  • Accelerated Hypothesis Generation for Multistructure Data via Preference Analysis

    Tat-Jun Chin;Jin Yu;D. Suter

  • Robust fitting of multiple structures: The statistical learning approach

    Tat-Jun Chin;Hanzi Wang;David Suter

  • Clustering with Hypergraphs: The Case for Large Hyperedges

    Pulak Purkait;Tat-Jun Chin;Alireza Sadri;David Suter

  • Seam-Driven Image Stitching

    Junhong Gao;Yu Li;Tat-Jun Chin;Michael S. Brown

  • The Random Cluster Model for robust geometric fitting

    Trung Thanh Pham;Tat-Jun Chin;Jin Yu;David Suter

  • A Multiple Hypothesis Tracker for Multitarget Tracking With Multiple Simultaneous Measurements

    Thuraiappah Sathyan;Tat-Jun Chin;Sanjeev Arulampalam;David Suter

  • End-to-End Learnable Geometric Vision by Backpropagating PnP Optimization

    Bo Chen;Alvaro Parra;Jiewei Cao;Nan Li

  • Fast Rotation Search with Stereographic Projections for 3D Registration

    Álvaro Joaquin Parra Bustos;Tat-Jun Chin;David Suter

  • Rotation Averaging and Strong Duality

    Anders Eriksson;Carl Olsson;Fredrik Kahl;Tat-Jun Chin

  • Clustering with Hypergraphs: The Case for Large Hyperedges

    Pulak Purkait;Tat-Jun Chin;Hanno Ackermann;David Suter

  • Efficient globally optimal consensus maximisation with tree search

    Tat-Jun Chin;Pulak Purkait;Anders Eriksson;David Suter

  • Auto-Rectify Network for Unsupervised Indoor Depth Estimation

    Unknown

  • Incremental kernel SVD for face recognition with image sets

    Tat Jun Chin;Konrad Schindler;David Suter

  • In defence of RANSAC for outlier rejection in deformable registration

    Quoc-Huy Tran;Tat-Jun Chin;Gustavo Carneiro;Michael S. Brown

Frequent Co-Authors

David Suter
David Suter Edith Cowan University
Ian Reid
Ian Reid University of Adelaide
Hanzi Wang
Hanzi Wang Xiamen University
Gustavo Carneiro
Gustavo Carneiro University of Surrey
Joo-Hwee Lim
Joo-Hwee Lim Agency for Science, Technology and Research
Frank Neumann
Frank Neumann University of Adelaide
Michael S. Brown
Michael S. Brown York University
Fredrik Kahl
Fredrik Kahl Chalmers University of Technology
Alireza Bab-Hadiashar
Alireza Bab-Hadiashar RMIT University

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