updates.md

Update Notes

We provide the details for important updates of YOLO-World in this note.

Model Architecture

[2024-2-29]: YOLO-World-v2:

1. We remove the I-PoolingAttention: though it improves the performance for zero-shot LVIS evaluation, it affects the inference speeds after exporting YOLO-World to ONNX or TensorRT. Considering the trade-off, we remove the I-PoolingAttention in the newest version.
2. We replace the L2-Norm in the contrastive head with the BatchNorm. The L2-Norm contains complex operations, such as reduce, which is time-consuming for deployment. However, the BatchNorm can be fused into the convolution, which is much more efficient and also improves the zero-shot performance.