This work contributes a large, complex, and realistic high-quality safety clothing and helmet detection (SFCHD) dataset. The dataset comprises 12,373 images, covering 7 categories, with a total of 50,558 labeled instances. All images are captured from factory surveillance cameras, encompassing 40 different scenes across two chemical plants. It is worth noting that our SFCHD dataset not only provides a rich set of training samples but also serves as a benchmark for the evaluation of various detection tasks, such as small object detection, and high-low light object detection.
Variants: SFCHD
This dataset is used in 1 benchmark:
Task | Model | Paper | Date |
---|---|---|---|
Object Detection | YOLOv8+SCALE | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | TOOD+SCALE | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | TOOD | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | YOLOv8 | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | VFNet+SCALE | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | VFNet | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | Faster RCNN | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | FCOS | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | YOLOv5 | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | FCOS+SCALE | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | RetinaNet | Large, Complex, and Realistic Safety … | 2023-06-03 |
Object Detection | SSD | Large, Complex, and Realistic Safety … | 2023-06-03 |
Recent papers with results on this dataset: