Dr David Hall
Research Scientist
General Information
Current Affiliations:
Commonwealth Science and Industrial Research Organization (CSIRO)
CSIRO Data 61
Past Affiliations:
Queensland University of Technology (QUT)
QUT Centre for Robotic Vision (QCR)
Australian Centre for Robotic Vision (ACRV)
Fields of Expertise:
Robotic Vision
Neural Fields
Machine Learning
Simulation
Contact: d20.hall@qut.edu.au
Github Page: https://github.com/david2611
Staff Profile: profile
Arxiv Profile: arxiv home
Hi, I am David Hall, research scientist at the Commonwealth Science and Industrial Research Organization (CSIRO) whose long-term goal is to see robots able to cope with the unpredictable real world.
I began this journey with my PhD on adaptable systems for autonomous weed species recognition as a part of the strategic investment in farm robotics (SIFR) team. Between 2018 and 2021 I have worked as part of the robotic vision challenge group within the Australian Centre of Robotic Vision (ACRV) and QUT Centre for Robotics designing challenges, benchmarks, and evaluation measures that assist emerging areas of robotic vision research.
As a part of the robotic vision challenge group, I have assisted in:
Defining the field of probabilistic object detection (PrOD)
Creating the probability-based detection quality (PDQ) evaluation measure
Developing a PrOD robotic vision challenge
Developing a scene understanding robotic vision challenge
I have continued my research in agricultural robotics, examining weed recognitions systems that can predict when they might fail, as well as investigations into the uses of implicit model representations for visual place recognition.
I have just begun working for CSIRO and am looking forward to producing more work that can bring sense and safety to useful autonomous systems.
Recent 1st Author Publications
This is a list of my recent published papers (i.e. papers published within 5 years that don't exist only on arxiv) where I was 1st author on the paper. For a complete list of all papers that I have been involved with, please go to my "All Publications" page.
Title: Reg-NF: Efficient Registration of Implicit Surfaces within Neural Fields
Authors: Stephen Hausler, David Hall, Sutharsan Mahendren, Peyman Moghadam
Year: 2024
Published in: ICRA 2024 (TBP)
Paper Link: reg-nf_arxiv
Bibtex: regnf-arxiv.bib
Note: Equal contribution with first author
Title: BenchBot environments for active robotics (BEAR): simulated data for active scene understanding research
Authors: David Hall, Ben Talbot, Suman Raj Bista, Haoyang Zhang, Rohan Smith, Feras Dayoub, Niko Suenderhauf
Year: 2022
Published in: International Journal for Robotics Research
Paper Link: https://doi.org/10.1177/02783649211069404
Bibtex: ijrr2022.bib
Title: Probabilstic Object Detection: Definition and Evaluation
Authors: David Hall, Feras Dayoub, John Skinner, Haoyang Zhang, Dimity Miller, Peter Corke, Gustavo Carneiro, Anelia Angelova, Niko Suenderhauf
Year: 2020
Published in: 2020 IEEE Winter Conference on Applications of Computer Vision
Manuscript Download Link: WACV2020-arxiv
Bibtex: prod2020.bib
Probability-based Detection Quality