Object detection with multi-level representations generated from deep high-resolution representation learning (HRNetV2h). This is an official implementation for our TPAMI paper "Deep High-Resolution Representation Learning for Visual Recognition". https://arxiv.org/abs/1908.07919
We set the image size to 800*1200 and only calculate the FLOPs statistics of Convolutional layers and Batch Normalization layers. For R-CNN, we set the number of ROIs to 512.
How do you calculate your FLOP?
I need the data.
Thanks a lot.