MenghanXia / CARAFE

This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures

Introduction

This Repo is the official CUDA implementation of ICCV 2019 Oral paper for CARAFE: Content-Aware ReAssembly of FEatures.

@inproceedings{Wang_2019_ICCV,
    title = {CARAFE: Content-Aware ReAssembly of FEatures},
    author = {Wang, Jiaqi and Chen, Kai and Xu, Rui and Liu, Ziwei and Loy, Chen Change and Lin, Dahua},
    booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
    month = {October},
    year = {2019}
}

Setup CARAFE

There are two ways to setup CARAFE.

A. Install mmcv which contains CARAFE.

CARAFE is supported in mmcv. You may install mmcv following the official guideline.

https://github.com/open-mmlab/mmcv

B. Compile CARAFE by yourself.

Requirements:

CUDA >= 9.0, Pytorch >= 1.3, Python >= 3.6

Git clone this repo.

git clone https://github.com/myownskyW7/CARAFE

Setup CARAFE in your own project.

cp -r ./CARAFE $Your_Project_Path$
cd $Your_Project_Path$/CARAFE
python setup.py develop
# or "pip install -v -e ."

Run gradient check to make sure the operator is successfully compiled

python grad_check.py

Applications

Projects with CARAFE operators

mmcv

mmdetection

mmediting