Rove-Tree-11: The not-so-Wild Rover. A hierarchically structured image dataset for deep metric learning research

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

19 Downloads (Pure)

Abstract

We present a new dataset of images of pinned insects from museum collections along with a ground truth phylogeny (a graph representing the relative evolutionary distance between species). The images include segmentations, and can be used for clustering and deep hierarchical metric learning. As far as we know, this is the first dataset released specifically for generating phylogenetic trees. We provide several benchmarks for deep metric learning using a selection of state-of-the-art methods.
Original languageEnglish
Title of host publicationComputer Vision – ACCV 2022 : 16th Asian Conference on Computer Vision, Macao, China, December 4–8, 2022, Proceedings, Part I
PublisherSpringer
Publication date2023
Pages2967-2983
Publication statusPublished - 2023
Event16th Asian Conference on Computer Vision, ACCV 2022 - Macao, China
Duration: 4 Dec 20228 Dec 2022

Conference

Conference16th Asian Conference on Computer Vision, ACCV 2022
Country/TerritoryChina
CityMacao
Period04/12/202208/12/2022
SeriesLecture Notes in Computer Science
Volume13841
ISSN0302-9743

Cite this