pkinet
Official implementation of CVPR2024 Paper "Poly Kernel Inception Network for Remote Sensing Detection".
Science Score: 44.0%
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○Scientific vocabulary similarity
Low similarity (5.6%) to scientific vocabulary
Repository
Official implementation of CVPR2024 Paper "Poly Kernel Inception Network for Remote Sensing Detection".
Basic Info
Statistics
- Stars: 69
- Watchers: 1
- Forks: 18
- Open Issues: 4
- Releases: 0
Metadata Files
README.md
Poly Kernel Inception Network for Remote Sensing Detection
Introduction
This repository is the official implementation of CVPR2024 Paper "Poly Kernel Inception Network for Remote Sensing Detection".
Results and models
Pretrained models
Imagenet 300-epoch pretrained PKINet-T backbone: Download
Imagenet 300-epoch pretrained PKINet-S backbone: Download
Experiments results
DOTAv1.0
| Model | mAP | Angle | Aug | Configs | Download | |:------------------------:|:-----:|:-----:| :-: |:------------------------------------------------------------------------------------------------------:|:--------------------------------------------------------------------------:| | PKINet-T (1024,1024,200) | 77.87 | le90 | - | pkinet-tfpno-rcnndotav1-ssle90 | model | | PKINet-S (1024,1024,200) | 78.39 | le90 | - | pkinet-sfpno-rcnndotav1-ssle90 | model|
DOTAv1.5
| Model | mAP | Angle | Aug | Configs | Download | |:------------------------:|:-----:|:-----:| :-: |:-------------------------------------------------------------------------------------------------------:|:----------------------------------------------------------------:| | PKINet-S (1024,1024,200) | 71.47 | le90 | - |pkinet-sfpno-rcnndotav15-ssle90 |model |
Installation
MMRotate-PKINet depends on PyTorch, MMCV and MMDetection. Below are quick steps for installation. Please refer to Install Guide for more detailed instruction.
shell
conda create --name openmmlab python=3.8 -y
conda activate openmmlab
conda install pytorch==1.11.0 torchvision==0.12.0 cudatoolkit=11.3 -c pytorch
pip install yapf==0.40.1
pip install -U openmim
mim install mmcv-full
mim install mmdet
mim install mmengine
git clone
cd PKINet
mim install -v -e .
Get Started
Please see get_started.md for the basic usage of MMRotate. We provide colab tutorial, and other tutorials for:
License
This project is released under the Apache 2.0 license.
Citation
@InProceedings{Cai_2024_Poly,
author = {Cai, Xinhao and Lai, Qiuxia and Wang, Yuwei and Wang, Wenguan and Sun, Zeren and Yao, Yazhou},
title = {Poly Kernel Inception Network for Remote Sensing Detection},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2024},
pages = {27706-27716}
}
Owner
- Login: PKINet
- Kind: user
- Repositories: 1
- Profile: https://github.com/PKINet
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this software, please cite it as below." authors: - name: "MMRotate Contributors" title: "OpenMMLab rotated object detection toolbox and benchmark" date-released: 2022-02-18 url: "https://github.com/open-mmlab/mmrotate" license: Apache-2.0
GitHub Events
Total
- Issues event: 10
- Watch event: 33
- Issue comment event: 13
Last Year
- Issues event: 10
- Watch event: 33
- Issue comment event: 13