attention-model

Attention mechanism Implementation for Keras.

Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation

Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet

Text classification using deep learning models in Pytorch

Neural Machine Translation with Keras

A Structured Self-attentive Sentence Embedding

Attention OCR Based On Tensorflow

The implementation of "End-to-End Multi-Task Learning with Attention" [CVPR 2019].

AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation

Implementation of the Swin Transformer in PyTorch.

Camouflaged Object Detection, CVPR 2020 (Oral)

This repository implements the the encoder and decoder model with attention model for OCR

A PyTorch reimplementation for paper Generative Image Inpainting with Contextual Attention (https://arxiv.org/abs/1801.07892)

PyTorch implementation of batched bi-RNN encoder and attention-decoder.

Code/Model release for NIPS 2017 paper "Attentional Pooling for Action Recognition"

👊 计算机视觉中用到的注意力模块和其他即插即用模块PyTorch Implementation Collection of Attention Module and Plug&Play Module

Bidirectional LSTM network for speech emotion recognition.

attention model for entailment on SNLI corpus implemented in Tensorflow and Keras

code of Relation Classification via Multi-Level Attention CNNs

Soft attention mechanism for video caption generation

Code & data accompanying the NAACL 2019 paper "Bidirectional Attentive Memory Networks for Question Answering over Knowledge Bases"

A neural network to generate captions for an image using CNN and RNN with BEAM Search.

A recurrent attention module consisting of an LSTM cell which can query its own past cell states by the means of windowed multi-head attention. The formulas are derived from the BN-LSTM and the Transformer Network. The LARNN cell with attention can be easily used inside a loop on the cell state, just like any other RNN. (LARNN)

A Keras-based library for analysis of time series data using deep learning algorithms.

Seq2SeqSharp is a tensor based fast & flexible encoder-decoder deep neural network framework written by .NET (C#). It has many highlighted features, such as automatic differentiation, many different types of encoders/decoders(Transformer, LSTM, BiLSTM and so on), multi-GPUs supported and so on.

Image Captioning based on Bottom-Up and Top-Down Attention model

ECG Classification

This repository contain various types of attention mechanism like Bahdanau , Soft attention , Additive Attention , Hierarchical Attention etc in Pytorch, Tensorflow, Keras

Pytorch implementation of Unsupervised Attention-guided Image-to-Image Translation.