The Ciona17 Dataset for Semantic Segmentation of Invasive Species in a Marine Aquaculture Environment
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Abstract (arXiv)
An original dataset for semantic segmentation, Ciona17, is introduced, which to the best of the authors' knowledge, is the first dataset of its kind with pixel-level annotations pertaining to invasive species in a marine environment. Diverse outdoor illumination, a range of object shapes, colour, and severe occlusion provide a significant real world challenge for the computer vision community. An accompanying ground-truthing tool for superpixel labeling, Truth and Crop, is also introduced. Finally, we provide a baseline using a variant of Fully Convolutional Networks, and report results in terms of the standard mean intersection over union (mIoU) metric.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Feb 2017.
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Citing papers per year: 2022: 1; 2023: 2; 2024: 1.
4 papers.
- 2023What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentationcited by 24
- 2024BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversitycited by 22
- 2023Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognitioncited by 11
- 2022Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposurecited by 1
- 2024BIOSCAN-5M: A Multimodal Dataset for Insect Biodiversity18 Jun 2024
- 2023Species196: A One-Million Semi-supervised Dataset for Fine-grained Species Recognition25 Sep 2023
- 2023What a MESS: Multi-Domain Evaluation of Zero-Shot Semantic Segmentation27 Jun 2023
- 2022Semantic Segmentation for Fully Automated Macrofouling Analysis on Coatings after Field Exposure21 Nov 2022