Rove-Tree-11: The Not-so-Wild Rover a Hierarchically Structured Image Dataset for Deep Metric Learning Research

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Documents

  • Rove-Tree-11

    Accepted author manuscript, 7.02 MB, PDF document

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, Proceedings
EditorsLei Wang, Juergen Gall, Tat-Jun Chin, Imari Sato, Rama Chellappa
PublisherSpringer
Publication date2023
Pages425-441
ISBN (Print)9783031263477
DOIs
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
LandChina
ByMacao
Periode04/12/202208/12/2022
SeriesLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13845 LNCS
ISSN0302-9743

Bibliographical note

Publisher Copyright:
© 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

    Research areas

  • Dataset, Hierarchical dataset, Hierarchy, Phylogenetic tree, Phylogeny, Rove, Staphylinidae, Tree

ID: 371021177