pkinet

Official implementation of CVPR2024 Paper "Poly Kernel Inception Network for Remote Sensing Detection".

https://github.com/pkinet/pkinet

Science Score: 44.0%

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Repository

Official implementation of CVPR2024 Paper "Poly Kernel Inception Network for Remote Sensing Detection".

Basic Info
  • Host: GitHub
  • Owner: PKINet
  • License: apache-2.0
  • Language: Python
  • Default Branch: main
  • Homepage:
  • Size: 9.78 MB
Statistics
  • Stars: 69
  • Watchers: 1
  • Forks: 18
  • Open Issues: 4
  • Releases: 0
Created over 2 years ago · Last pushed almost 2 years ago
Metadata Files
Readme Contributing License Citation

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

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

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