UAVid is a high-resolution UAV semantic segmentation dataset as a complement, which brings new challenges, including large scale variation, moving object recognition and temporal consistency preservation. The UAV dataset consists of 30 video sequences capturing 4K high-resolution images in slanted views. In total, 300 images have been densely labeled with 8 classes for the semantic labeling task.
Source: UAVid: A Semantic Segmentation Dataset for UAV Imagery
Image Source: https://uavid.nl/
Variants: UAVid
This dataset is used in 2 benchmarks:
| Task | Model | Paper | Date |
|---|---|---|---|
| Semantic Segmentation | D2LS | Dynamic Dictionary Learning for Remote … | 2025-03-09 |
| Semantic Segmentation | LWGANet L2 | LWGANet: A Lightweight Group Attention … | 2025-01-17 |
| Semantic Segmentation | LSKNet-T | LSKNet: A Foundation Lightweight Backbone … | 2024-03-18 |
| Semantic Segmentation | LSKNet-S | LSKNet: A Foundation Lightweight Backbone … | 2024-03-18 |
| Semantic Segmentation | UNetFormer | UNetFormer: A UNet-like Transformer for … | 2021-09-18 |
| Scene Segmentation | UNetFormer | UNetFormer: A UNet-like Transformer for … | 2021-09-18 |
| Semantic Segmentation | BANet | Transformer Meets Convolution: A Bilateral … | 2021-06-23 |
Recent papers with results on this dataset: