NDD20: A large-scale few-shot dolphin dataset for coarse and fine-grained categorisation

Abstract

We introduce the Northumberland Dolphin Dataset 2020 (NDD20), a challenging image dataset annotated for both coarse and fine-grained instance segmentation and categorisation. This dataset, the first release of the NDD, was created in response to the rapid expansion of computer vision into conservation research and the production of field-deployable systems suited to extreme environmental conditions -- an area with few open source datasets. NDD20 contains a large collection of above and below water images of two different dolphin species for traditional coarse and fine-grained segmentation. All data contained in NDD20 was obtained via manual collection in the North Sea around the Northumberland coastline, UK. We present experimentation using standard deep learning network architecture trained using NDD20 and report baselines results.

arXiv comment5 pages, 6 figures, download link, submitted to FGVC7 Workshop @ CVPR20

References in corpus (5)

• SGDR: Stochastic Gradient Descent with Warm Restarts
• The VIA Annotation Software for Images, Audio and Video
• The iWildCam 2019 Challenge Dataset
• Unsupervised Threshold for Automatic Extraction of Dolphin Dorsal Fin Outlines from Digital Photographs in DARWIN (Digital Analysis and Recognition of Whale Images on a Network)
• The Northumberland Dolphin Dataset: A Multimedia Individual Cetacean Dataset for Fine-Grained Categorisation