🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐

A PyTorch implementation of the Transformer model in "Attention is All You Need".

EPSANet：An Efficient Pyramid Split Attention Block on Convolutional Neural Network

Official implement of "CAT: Cross Attention in Vision Transformer".

Kuan-Chieh Wang, Paul Vicol, Eleni Triantafillou, Richard Zemel. (2020). “Few-shot Out-of-Distribution Detection.” (ICML) Workshop on Uncertainty and Robustness in Deep Learning

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

Incremental Few-shot Text Classification with Multi-round New Classes: Formulation, Dataset and System. NAACL 2021. https://arxiv.org/abs/2104.11882

The code of "Few-Shot Event Detection with Prototypical Amortized Conditional Random Field", Findings of ACL 2021

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

S. Liu, Q. Shi and L. Zhang, "Few-Shot Hyperspectral Image Classification With Unknown Classes Using Multitask Deep Learning," in IEEE Transactions on Geoscience and Remote Sensing, doi: 10.1109/TG…

Code for ECA-Net: Efficient Channel Attention for Deep Convolutional Neural Networks

Code accompanying the paper 'Incremental Few-Shot Instance Segmentation'

This is the code for the paper Siamese-Prototype Netwrok for Few-Shot Remote Sensing Image Scene Classification

Implementation of Non-local Block.

Spatial Contrastive Learning for Few-Shot Classification.

(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks

This repository contains the code to reproduce the few-shot classification experiments carried out in our paper Revisiting Deep Local Descriptor for Improved Few-Shot Classification.

ICLR 2021: A Universal Representation Transformer Layer for Few-Shot Image Classification

Pytorch Code for "A Broad Study on the Transferability of Visual Representations with Contrastive Learning"

Gluon CV Toolkit

Deformable Convolutional Networks

Codebase for Embedding Propagation: Smoother Manifold for Few-Shot Classification

deep learning for image processing including classification and object-detection etc.

Implementation of One-Shot Object Detection with Co-Attention and Co-Excitation in Pytorch