How this analysis was created: This summary and feature list are AI-generated from collected project material and can contain mistakes. Stars, license and language are imported from GitHub. Inclusion does not mean that we have tested or audited this project. Check the source documentation for any feature you depend on. Learn more on our About page.
This repository contains the code (in PyTorch) for SlimConv: Reducing Channel Redundancy in Convolutional Neural Networks by Features Recombining paper (TIP 2021)
The main features of jiaxiongq/slimconv are: Plug and Play Modules.
Projects with overlapping indexed features include: andrew-qibin/spnet — This repository is a PyTorch implementation for our CVPR2020 paper (non-commercial use only). d-li14/psconv — [ECCV 2020] PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer. dingxiaoh/acnet — Update (Aug 17, 2021): refactored the code of ACB. The readability has been greatly improved. You may call… goatmessi7/rfbnet — By Songtao Liu, Di Huang, Yunhong Wang. hszhao/pspnet — by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. iduta/pyconv — This is the PyTorch implementation of our paper "Pyramidal Convolution: Rethinking Convolutional Neural Networks for…
ECCV 2020 PSConv: Squeezing Feature Pyramid into One Compact Poly-Scale Convolutional Layer
Update (Aug 17, 2021): refactored the code of ACB. The readability has been greatly improved. You may call switchtodeploy of an ACB to convert it to the inference-time structure. If you use ACB in your own model, the conversion is as easy as `` for m in yourmodel.modules(): if hasattr(m,…
This repository is a PyTorch implementation for our CVPR2020 paper (non-commercial use only).
