Python Pretrained-dcnn-attention-ser Resources

PyTorch reimplementation of the paper Swin Transformer V2: Scaling Up Capacity and Resolution [arXiv 2021].

Action Transformer A Self-Attention Model for Short-Time Human Action Recognition This repository contains the official TensorFlow implementation of t

AAF framework Framework generalities This repository contains the code of the AAF framework proposed in this paper. The main idea behind this work is

A minimal yet resourceful implementation of diffusion models (along with pretrained models + synthetic images for nine datasets)

ReLA (Rectified Linear Attention) Transformer Implementation of a Transformer using ReLA (Rectified Linear Attention). It will also contain an attempt

NLP Best Practices In recent years, natural language processing (NLP) has seen quick growth in quality and usability, and this has helped to drive bus

NLP-Models-Tensorflow, Gathers machine learning and tensorflow deep learning models for NLP problems, code simplify inside Jupyter Notebooks 100%. Tab

Jogo de DadoX Projeto de script que simula um Jogo de dados em Python 3 onde é definido o lado a ser apostado (1, 2, 3, 4, 5 e 6) ou se vai ser um núm

MVS2D: Efficient Multi-view Stereo via Attention-Driven 2D Convolutions Project Page | Paper If you find our work useful for your research, please con

CenterGroup This the official implementation of our ICCV 2021 paper The Center of Attention: Center-Keypoint Grouping via Attention for Multi-Person P

Multi-Time Attention Networks (mTANs) This repository contains the PyTorch implementation for the paper Multi-Time Attention Networks for Irregularly

Trans_attention_vis This is a super simple visualization toolbox (script) for transformer attention visualization ✌ 1. How to prepare your attention m

RaftMLP RaftMLP: How Much Can Be Done Without Attention and with Less Spatial Locality? By Yuki Tatsunami and Masato Taki (Rikkyo University) [arxiv]

timmFasterRcnn model_config.py - it returns the model,feat_sizes,output channel and the feat layer names, which is reqd by the Add_FPN.py file Add_FP

cdf_att_classification classes = {0: 'cat', 1: 'dog', 2: 'flower'} In this project we use both Resnet and Self-attention layer for cdf-Classification.

The CodeSearchNet challenge has been concluded We would like to thank all participants for their submissions and we hope that this challenge provided

GAT - Graph Attention Network (PyTorch) 💻 + graphs + 📣 = ❤️ This repo contains a PyTorch implementation of the original GAT paper ( 🔗 Veličković et

Fast convergence of detr with spatially modulated co-attention Usage There are no extra compiled components in SMCA DETR and package dependencies are

SCOUTER: Slot Attention-based Classifier for Explainable Image Recognition PDF Abstract Explainable artificial intelligence has been gaining attention

Block Sparse Attention 研究总结 本人近半年来对Block Sparse Attention（块稀疏注意力）的研究总结（持续更新中）。按时间顺序，主要分为如下三部分： PyTorch 自定义 CUDA 算子——以矩阵乘法为例 基于 Triton 的 Block Sparse A

Attention-based Transformation from Latent Features to Point Clouds This repository contains a PyTorch implementation of the paper: Attention-based Tr

bottom-up-attention This code implements a bottom-up attention model, based on multi-gpu training of Faster R-CNN with ResNet-101, using object and at

Detection of Fake Reviews on Online Review Platforms using Deep Learning Architectures Dataset: https://s3.amazonaws.com/fast-ai-nlp/yelp_review_polar

SAFL: A Self-Attention Scene Text Recognizer with Focal Loss This repository implements the SAFL in pytorch. Installation conda env create -f environm

CV Backbones including GhostNet, TinyNet, TNT (Transformer in Transformer) developed by Huawei Noah's Ark Lab. GhostNet Code TinyNet Code TNT Code Pyr

Contents Semantic Image Synthesis with DAGAN Installation Dataset Preparation Generating Images Using Pretrained Model Train and Test New Models Evalu

AttentionGAN-v2 for Unpaired Image-to-Image Translation AttentionGAN-v2 Framework The proposed generator learns both foreground and background attenti

connect-caption-and-trace This repository contains the reference code for our paper Connecting What to Say With Where to Look by Modeling Human Attent

Introduction This repository is for X-Linear Attention Networks for Image Captioning (CVPR 2020). The original paper can be found here. Please cite wi

Adaptively Aligned Image Captioning via Adaptive Attention Time This repository includes the implementation for Adaptively Aligned Image Captioning vi

SA-tensorflow Tensorflow implementation of soft-attention mechanism for video caption generation. An example of soft-attention mechanism. The attentio

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

Introduction This neural system for image captioning is roughly based on the paper "Show, Attend and Tell: Neural Image Caption Generation with Visual

Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth Estimation This is the official implementation for the method described in Ch

AlexaUsingPython - Alexa will pay attention to your order, as: Hello Alexa, play music, Hello Alexa, what's the time? Alexa will pay attention to your order, get it, and afterward do some activity as indicated by your order.

A collection of graph classification methods, covering embedding, deep learning, graph kernel and factorization papers

[UPDATED] A TensorFlow Implementation of Attention Is All You Need When I opened this repository in 2017, there was no official code yet. I tried to i

Easily train or fine-tune SOTA computer vision models from one training repository. SuperGradients Introduction Welcome to SuperGradients, a free open

Shunted Transformer This is the offical implementation of Shunted Self-Attention via Multi-Scale Token Aggregation by Sucheng Ren, Daquan Zhou, Shengf

SEAM The implementation of Self-supervised Equivariant Attention Mechanism for Weakly Supervised Semantic Segmentaion. You can also download the repos

SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th

Graph-Bert Source code of "Graph-Bert: Only Attention is Needed for Learning Graph Representations". Please check the script.py as the entry point. We

[TensorFlow 2] Attention is all you need (Transformer) TensorFlow implementation of "Attention is all you need (Transformer)" Dataset The MNIST datase

SAG-DTA The code is the implementation for the paper 'SAG-DTA: Prediction of Drug–Target Affinity Using Self-Attention Graph Network'. Requirements py

Embeddings Embeddings is a python package that provides pretrained word embeddings for natural language processing and machine learning. Instead of lo

XViT - Space-time Mixing Attention for Video Transformer This is the official implementation of the XViT paper: @inproceedings{bulat2021space, title

Attention for PyTorch with Linear Memory Footprint Unofficially implements https://arxiv.org/abs/2112.05682 to get Linear Memory Cost on Attention (+

ALiBi PyTorch implementation of Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation. Quickstart Clone this reposit

Hierarchical Attention Mining (HAM) for weakly-supervised abnormality localization This is the official PyTorch implementation for the HAM method. Pap

Multi-Probe Attention for Semantic Indexing About This project is developed for the topic of COVID-19 semantic indexing. Directories & files A. The di

memory_efficient_attention.pytorch A human-readable PyTorch implementation of "Self-attention Does Not Need O(n^2) Memory" (Rabe&Staats'21). def effic

Weak-supervised Visual Geo-localization via Attention-based Knowledge Distillation Introduction WAKD is a PyTorch implementation for our ICPR-2022 pap

ttslearn: Library for Pythonで学ぶ音声合成 (Text-to-speech with Python) 日本語は以下に続きます (Japanese follows) English: This book is written in Japanese and primaril

D-HAN The source code of D-HAN This is the source code of D-HAN: Dynamic News Recommendation with Hierarchical Attention Network. However, only the co

DSAMNet The pytorch implementation for "A Deeply-supervised Attention Metric-based Network and an Open Aerial Image Dataset for Remote Sensing Change

CoANet: Connectivity Attention Network for Road Extraction From Satellite Imagery This paper (CoANet) has been published in IEEE TIP 2021. This code i

Locally-Shifted-Attention-With-Early-Global-Integration Pretrained models You can download all the models from here. Training Imagenet python -m torch

A-ESRGAN: Training Real-World Blind Super-Resolution with Attention-based U-net Discriminators The authors are hidden for the purpose of double blind

Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo

Table of contents Introduction Using BARTpho with fairseq Using BARTpho with transformers Notes BARTpho: Pre-trained Sequence-to-Sequence Models for V

Show, Attend and Tell Update (December 2, 2016) TensorFlow implementation of Show, Attend and Tell: Neural Image Caption Generation with Visual Attent

SelectionGAN for Guided Image-to-Image Translation CVPR Paper | Extended Paper | Guided-I2I-Translation-Papers Citation If you use this code for your

Memory Efficient Attention This is unofficial implementation of Self-attention Does Not Need O(n^2) Memory for Jax and PyTorch. Implementation is almo

Vision-aided GAN video (3m) | website | paper Can the collective knowledge from a large bank of pretrained vision models be leveraged to improve GAN t

Pose-Transfer Code for the paper Progressive Pose Attention for Person Image Generation in CVPR19(Oral). The paper is available here. Video generation

PUREPLES - Pure Python Library for ES-HyperNEAT About This is a library of evolutionary algorithms with a focus on neuroevolution, implemented in pure

GANformer: Generative Adversarial Transformers Drew A. Hudson* & C. Lawrence Zitnick Update: We released the new GANformer2 paper! *I wish to thank Ch

CPT This repository contains code and checkpoints for CPT. CPT: A Pre-Trained Unbalanced Transformer for Both Chinese Language Understanding and Gener

Edge-augmented Graph Transformer Introduction This is the official implementation of the Edge-augmented Graph Transformer (EGT) as described in https:

Pretrained Language Model This repository provides the latest pretrained language models and its related optimization techniques developed by Huawei N

Nystromformer: A Nystrom-based Algorithm for Approximating Self-Attention April 6, 2021 We extended segment-means to compute landmarks without requiri

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

Pay Attention when Required (PAR) Transformer-XL An implementation of the Pay Attention when Required transformer from the paper: https://arxiv.org/pd

Routing Transformer A fully featured implementation of Routing Transformer. The paper proposes using k-means to route similar queries / keys into the

Linear Multihead Attention (Linformer) PyTorch Implementation of reproducing the Linear Multihead Attention introduced in Linformer paper (Linformer:

DeBERTa: Decoding-enhanced BERT with Disentangled Attention This repository is the official implementation of DeBERTa: Decoding-enhanced BERT with Dis

Status: Archive (code is provided as-is, no updates expected) Update August 2020: For an example repository that achieves state-of-the-art modeling pe

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

PyContinual (An Easy and Extendible Framework for Continual Learning) Easy to Use You can sumply change the baseline, backbone and task, and then read

Transformer for Image Colorization This is an implemention for Yes, "Attention Is All You Need", for Exemplar based Colorization, and the current soft

Mask2Former: Masked-attention Mask Transformer for Universal Image Segmentation in TensorFlow 2 Bowen Cheng, Ishan Misra, Alexander G. Schwing, Alexan

This repository is the official implementation of the Hybrid Self-Attention NEAT algorithm. It contains the code to reproduce the results presented in the original paper: https://arxiv.org/abs/2112.03670

TRACER: Extreme Attention Guided Salient Object Tracing Network This paper was accepted at AAAI 2022 SA poster session. Datasets All datasets are avai

Ex-model CL Ex-model continual learning is a setting where a stream of experts (i.e. model's parameters) is available and a CL model learns from them

Transcription Factor binding predictions with Attention and Transformers A repository with exploration into using transformers to predict DNA ↔ transc

(Preprint) Official PyTorch implementation of "How Do Vision Transformers Work?"

PyTorch implementation of Video Transformer Benchmarks This repository is mainly built upon Pytorch and Pytorch-Lightning. We wish to maintain a colle

Winning submission to the 2021 Brain Tumor Segmentation Challenge This repo contains the codes and pretrained weights for the winning submission to th

HetGAN Implementation of Heterogeneous Graph Attention Network This is the code repository of paper "Prediction of Metro Ridership During the COVID-19

Do pedestrians pay attention? Eye contact detection for autonomous driving Official implementation of the paper Do pedestrians pay attention? Eye cont

DRSAN A Dynamic Residual Self-Attention Network for Lightweight Single Image Super-Resolution Karam Park, Jae Woong Soh, and Nam Ik Cho Environments U

Winning submission to the 2021 Brain Tumor Segmentation Challenge This repo contains the codes and pretrained weights for the winning submission to th

Introduction 1. Usage (For MSS) 1.1 Prepare running environment 1.2 Use pretrained model 1.3 Train new MSS models from scratch 1.3.1 How to train 1.3.

Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"

Torch-template-for-deep-learning Pytorch implementations of some **classical backbone CNNs, data enhancement, torch loss, attention, visualization and

END TO END ASR TRANSFORMER 本项目基于transformer 6*encoder+6*decoder的基本结构构造的端到端的语音识别系统 Model Instructions 1.数据准备: 自行下载数据，遵循文件结构如下： ├── data │ ├── train │

Introduction This repo contains code for reproducing the results in the paper Graphical Models with Attention for Context-Specific Independence and an

ADD: Frequency Attention and Multi-View based Knowledge Distillation to Detect Low-Quality Compressed Deepfake Images Binh M. Le & Simon S. Woo, "ADD:

Pretrained Cost Model for Distributed Constraint Optimization Problems Requirements PyTorch 1.9.0 PyTorch Geometric 1.7.1 Directory structure baseline