WildlifeDatasets: An open-source toolkit for animal re-identification

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43972904" target="_blank" >RIV/49777513:23520/24:43972904 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21230/24:00377620
Result on the web
<a href="https://ieeexplore.ieee.org/document/10483925" target="_blank" >https://ieeexplore.ieee.org/document/10483925</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/WACV57701.2024.00585" target="_blank" >10.1109/WACV57701.2024.00585</a>

Result language
angličtina
Original language name
WildlifeDatasets: An open-source toolkit for animal re-identification
Original language description
In this paper, we present WildlifeDatasets – an open-source toolkit intended primarily for ecologists and computer-vision / machine-learning researchers. The WildlifeDatasets is written in Python, allows straightforward access to publicly available wildlife datasets, and provides a wide variety of methods for dataset pre-processing, performance analysis, and model fine-tuning. We show-case the toolkit in various scenarios and baseline experiments, including, to the best of our knowledge, the most comprehensive experimental comparison of datasets and methods for wildlife re-identification, including both local descriptors and deep learning approaches. Furthermore, we provide the first-ever foundation model for individual re-identification within a wide range of species – MegaDescriptor – that provides state-of-the-art performance on animal re-identification datasets and outperforms other pre-trained models such as CLIP and DINOv2 by a significant margin. To make the model available to the general public and to allow easy integration with any existing wildlife monitoring applications, we provide multiple MegaDescriptor flavors (i.e., Small, Medium, and Large) through the HuggingFace hub.
Czech name
—
Czech description
—

Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2024
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
2024 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
ISBN
979-8-3503-1892-0
ISSN
2472-6737
e-ISSN
2642-9381
Number of pages
11
Pages from-to
5941-5951
Publisher name
Institute of Electrical and Electronics Engineers Inc.
Place of publication
Piscataway
Event location
Waikoloa, HI, USA
Event date
Jan 3, 2024
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
001222964606009

Similar results(10)