In this report, we present PP-YOLOE, an industrial state-of-the-art object detector with high performance and friendly deployment.
Ranked #1 on 2D object detection on BDD100K
The brain is the perfect place to look for inspiration to develop more efficient neural networks.
To meet these two concerns, we comprehensively evaluate a collection of existing refinements to improve the performance of PP-YOLO while almost keep the infer time unchanged.
However, the high-dimensional embedding obtained via 1-D convolution and positional encoding can lead to the loss of the signal's own temporal information and a large amount of training parameters.