Segmentation of Underwater IMagery
The Segmentation of Underwater IMagery (SUIM) dataset contains over 1500 images with pixel annotations for eight object categories: fish (vertebrates), reefs (invertebrates), aquatic plants, wrecks/ruins, human divers, robots, and sea-floor. The images have been rigorously collected during oceanic explorations and human-robot collaborative experiments, and annotated by human participants.
Source: Semantic Segmentation of Underwater Imagery: Dataset and Benchmark
Image Source: http://irvlab.cs.umn.edu/resources/suim-dataset
Variants: SUIM
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Unsupervised Semantic Segmentation | DatUS (ViT-B/8) + OC | DatUS^2: Data-driven Unsupervised Semantic Segmentation … | 2024-01-23 |
| Unsupervised Semantic Segmentation | DatUS (ViT-B/8) | DatUS^2: Data-driven Unsupervised Semantic Segmentation … | 2024-01-23 |
Recent papers with results on this dataset: