SODA-D is a large-scale dataset tailored for small object detection in driving scenario, which is built on top of MVD dataset and owned data, where the former is a dataset dedicated to pixel-level understanding of street scenes, and the latter is mainly captured by onboard cameras and mobile phones. With 24704 well-chosen and high-quality images of driving scenarios, SODA-D comprises 277596 instances of 9 categories with horizontal bounding boxes.
Variants: SODA-D
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Small Object Detection | CFINet | Small Object Detection via Coarse-to-fine … | 2023-08-18 |
Recent papers with results on this dataset: