PhraseCut is a dataset consisting of 77,262 images and 345,486 phrase-region pairs. The dataset is collected on top of the Visual Genome dataset and uses the existing annotations to generate a challenging set of referring phrases for which the corresponding regions are manually annotated.
Source: PhraseCut: Language-based Image Segmentation in the Wild
Image Source: https://people.cs.umass.edu/~chenyun/publication/phrasecut/
Variants: PhraseCut
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Referring Expression Segmentation | GROUNDHOG | GROUNDHOG: Grounding Large Language Models … | 2024-02-26 |
| Referring Expression Segmentation | GLIPv2 | GLIPv2: Unifying Localization and Vision-Language … | 2022-06-12 |
| Referring Expression Segmentation | MDETR ENB3 | MDETR -- Modulated Detection for … | 2021-04-26 |
| Referring Expression Segmentation | HULANet | PhraseCut: Language-based Image Segmentation in … | 2020-08-03 |
| Referring Expression Segmentation | RMI | PhraseCut: Language-based Image Segmentation in … | 2020-08-03 |
| Referring Expression Segmentation | MattNet | PhraseCut: Language-based Image Segmentation in … | 2020-08-03 |
Recent papers with results on this dataset: