Small object detection is the task of detecting small objects.
( Image credit: Feature-Fused SSD )
As DenseNet conserves intermediate features with diverse receptive fields by aggregating them with dense connection, it shows good performance on the object detection task.
We propose a multi-level feature fusion method for introducing contextual information in SSD, in order to improve the accuracy for small objects.
We evaluate different pasting augmentation strategies, and ultimately, we achieve 9. 7\% relative improvement on the instance segmentation and 7. 1\% on the object detection of small objects, compared to the current state of the art method on
For most of the object detectors based on multi-scale feature maps, the shallow layers are mainly responsible for small object detection due to their fine details.