Cascade RPN
April 4, 2022 ยท View on GitHub
We provide the code for reproducing experiment results of Cascade RPN.
@inproceedings{vu2019cascade,
title={Cascade RPN: Delving into High-Quality Region Proposal Network with Adaptive Convolution},
author={Vu, Thang and Jang, Hyunjun and Pham, Trung X and Yoo, Chang D},
booktitle={Conference on Neural Information Processing Systems (NeurIPS)},
year={2019}
}
Benchmark
Region proposal performance
| Method | Backbone | Style | Mem (GB) | Train time (s/iter) | Inf time (fps) | AR 1000 | Download |
|---|---|---|---|---|---|---|---|
| CRPN | R-50-FPN | caffe | - | - | - | 72.0 | model |
Detection performance
| Method | Proposal | Backbone | Style | Schedule | Mem (GB) | Train time (s/iter) | Inf time (fps) | box AP | Download |
|---|---|---|---|---|---|---|---|---|---|
| Fast R-CNN | Cascade RPN | R-50-FPN | caffe | 1x | - | - | - | 39.9 | model |
| Faster R-CNN | Cascade RPN | R-50-FPN | caffe | 1x | - | - | - | 40.4 | model |