The experiments showcase a variety of visualizations demonstrating the effectiveness of promptable segmentation and open-vocabulary segmentation techniques across different datasets.
Our findings reveal significant advancements in segmentation methodologies, highlighting their ability to adapt to diverse datasets and enhance visual comprehension.
By applying promptable segmentation, we effectively engage users' input to refine segmentation quality, thereby supporting both controlled and flexible visual analysis.
Open-vocabulary segmentation allows models to interpret and segment new, unseen categories, freeing them from the constraints of fixed vocabulary, which considerably expands usability.
Collection
[
|
...
]