Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Last update: Jan 08, 2023

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Deep Learning SA-Net

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)

By Qing-Long Zhang and Yu-Bin Yang

[State Key Laboratory for Novel Software Technology at Nanjing University]

Approach

Figure 1: The Diagram of a shuffle attention module.

Owner

Qing-Long Zhang

Machine Learning Bricklayer

GitHub Repository

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Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Related tags

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)

Approach

Owner

Qing-Long Zhang

PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)

Transfer Learning Shootout for PyTorch's model zoo (torchvision)

Python program that works as a contact list

learned_optimization: Training and evaluating learned optimizers in JAX

Simple Python application to transform Serial data into OSC messages

AWS provides a Python SDK, "Boto3" ,which can be used to access the AWS-account from the local.

Hardware-accelerated DNN model inference ROS2 packages using NVIDIA Triton/TensorRT for both Jetson and x86_64 with CUDA-capable GPU

ConvMAE: Masked Convolution Meets Masked Autoencoders

Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight

Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021

Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"

A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》

A Flow-based Generative Network for Speech Synthesis

Code for the paper "Graph Attention Tracking". (CVPR2021)

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Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style"

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Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

Related tags

Overview

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks (paper)

Approach

Owner

Qing-Long Zhang

PyTorch code for our paper "Image Super-Resolution with Non-Local Sparse Attention" (CVPR2021).

ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)

Transfer Learning Shootout for PyTorch's model zoo (torchvision)

Python program that works as a contact list

learned_optimization: Training and evaluating learned optimizers in JAX

Simple Python application to transform Serial data into OSC messages

AWS provides a Python SDK, "Boto3" ,which can be used to access the AWS-account from the local.

Hardware-accelerated DNN model inference ROS2 packages using NVIDIA Triton/TensorRT for both Jetson and x86_64 with CUDA-capable GPU

ConvMAE: Masked Convolution Meets Masked Autoencoders

Image super-resolution (SR) is a fast-moving field with novel architectures attracting the spotlight

Region-aware Contrastive Learning for Semantic Segmentation, ICCV 2021

Code for ICCV2021 paper PARE: Part Attention Regressor for 3D Human Body Estimation

Official implementation of the article "Unsupervised JPEG Domain Adaptation For Practical Digital Forensics"

A Pytorch reproduction of Range Loss, which is proposed in paper 《Range Loss for Deep Face Recognition with Long-Tailed Training Data》

A Flow-based Generative Network for Speech Synthesis

Code for the paper "Graph Attention Tracking". (CVPR2021)

CSE-519---Project - Job Title Analysis (Project for CSE 519 - Data Science Fundamentals)

Keras Implementation of Neural Style Transfer from the paper "A Neural Algorithm of Artistic Style"

All materials of Cassandra Event, Udyam'22

Weakly Supervised Segmentation by Tensorflow.

SA-Net: Shuffle Attention for Deep Convolutional Neural Networks _(paper)