764 Repositories
Python rq-vae-transformer Libraries
VD-BERT: A Unified Vision and Dialog Transformer with BERT
VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia
Codes for TS-CAM: Token Semantic Coupled Attention Map for Weakly Supervised Object Localization.
TS-CAM: Token Semantic Coupled Attention Map for Weakly SupervisedObject Localization This is the official implementaion of paper TS-CAM: Token Semant
The official implementation of VAENAR-TTS, a VAE based non-autoregressive TTS model.
VAENAR-TTS This repo contains code accompanying the paper "VAENAR-TTS: Variational Auto-Encoder based Non-AutoRegressive Text-to-Speech Synthesis". Sa
Simple transformer model for CIFAR10
CIFAR-Transformer Simple transformer model for CIFAR10. Reference: https://www.tensorflow.org/text/tutorials/transformer https://github.com/huggingfac
VD-BERT: A Unified Vision and Dialog Transformer with BERT
VD-BERT: A Unified Vision and Dialog Transformer with BERT PyTorch Code for the following paper at EMNLP2020: Title: VD-BERT: A Unified Vision and Dia
Global Filter Networks for Image Classification
Global Filter Networks for Image Classification Created by Yongming Rao, Wenliang Zhao, Zheng Zhu, Jiwen Lu, Jie Zhou This repository contains PyTorch
Pytorch implementation of “Recursive Non-Autoregressive Graph-to-Graph Transformer for Dependency Parsing with Iterative Refinement”
Graph-to-Graph Transformers Self-attention models, such as Transformer, have been hugely successful in a wide range of natural language processing (NL
multimodal transformer
This repo holds the code to perform experiments with the multimodal autoregressive probabilistic model Transflower. Overview of the repo It is structu
Unofficial implementation of "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" (https://arxiv.org/abs/2103.14030)
Swin-Transformer-Tensorflow A direct translation of the official PyTorch implementation of "Swin Transformer: Hierarchical Vision Transformer using Sh
Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2
Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot
Implementation of the GBST block from the Charformer paper, in Pytorch
Charformer - Pytorch Implementation of the GBST (gradient-based subword tokenization) module from the Charformer paper, in Pytorch. The paper proposes
The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"
Swin-Unet The codes for the work "Swin-Unet: Unet-like Pure Transformer for Medical Image Segmentation"(https://arxiv.org/abs/2105.05537). A validatio
Semi-Autoregressive Transformer for Image Captioning
Semi-Autoregressive Transformer for Image Captioning Requirements Python 3.6 Pytorch 1.6 Prepare data Please use git clone --recurse-submodules to clo
CLIP: Connecting Text and Image (Learning Transferable Visual Models From Natural Language Supervision)
CLIP (Contrastive Language–Image Pre-training) Experiments (Evaluation) Model Dataset Acc (%) ViT-B/32 (Paper) CIFAR100 65.1 ViT-B/32 (Our) CIFAR100 6
The implementation of "Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer"
Shuffle Transformer The implementation of "Shuffle Transformer: Rethinking Spatial Shuffle for Vision Transformer" Introduction Very recently, window-
This is an official implementation for "Video Swin Transformers".
Video Swin Transformer By Ze Liu*, Jia Ning*, Yue Cao, Yixuan Wei, Zheng Zhang, Stephen Lin and Han Hu. This repo is the official implementation of "V
Speech Recognition for Uyghur using Speech transformer
Speech Recognition for Uyghur using Speech transformer Training: this model using CTC loss and Cross Entropy loss for training. Download pretrained mo
A PyTorch Implementation of ViT (Vision Transformer)
ViT - Vision Transformer This is an implementation of ViT - Vision Transformer by Google Research Team through the paper "An Image is Worth 16x16 Word
Episodic Transformer (E.T.) is a novel attention-based architecture for vision-and-language navigation. E.T. is based on a multimodal transformer that encodes language inputs and the full episode history of visual observations and actions.
Episodic Transformers (E.T.) Episodic Transformer for Vision-and-Language Navigation Alexander Pashevich, Cordelia Schmid, Chen Sun Episodic Transform
LieTransformer: Equivariant Self-Attention for Lie Groups
LieTransformer This repository contains the implementation of the LieTransformer used for experiments in the paper LieTransformer: Equivariant Self-At
Aggragrating Nested Transformer Official Jax Implementation
NesT is a simple method, which aggragrates nested local transformers on image blocks. The idea makes vision transformers attain better accuracy, data efficiency, and convergence on the ImageNet benchmark. NesT can be scaled to small datasets to match convnet accuracy.
PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer
Official code Cross-Covariance Image Transformer (XCiT)
Official pytorch implement for “Transformer-Based Source-Free Domain Adaptation”
Official implementation for TransDA Official pytorch implement for “Transformer-Based Source-Free Domain Adaptation”. Overview: Result: Prerequisites:
PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer
Cross-Covariance Image Transformer (XCiT) PyTorch implementation and pretrained models for XCiT models. See XCiT: Cross-Covariance Image Transformer L
Implementation of Uformer, Attention-based Unet, in Pytorch
Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi
Tensorflow implementation of Swin Transformer model.
Swin Transformer (Tensorflow) Tensorflow reimplementation of Swin Transformer model. Based on Official Pytorch implementation. Requirements tensorflow
The codes and models in 'Gaze Estimation using Transformer'.
GazeTR We provide the code of GazeTR-Hybrid in "Gaze Estimation using Transformer". We recommend you to use data processing codes provided in GazeHub.
Official implementation of "SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers"
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers Figure 1: Performance of SegFormer-B0 to SegFormer-B5. Project page
Code for STFT Transformer used in BirdCLEF 2021 competition.
STFT_Transformer Code for STFT Transformer used in BirdCLEF 2021 competition. The STFT Transformer is a new way to use Transformers similar to Vision
This is the official implementation for "Do Transformers Really Perform Bad for Graph Representation?".
Graphormer By Chengxuan Ying, Tianle Cai, Shengjie Luo, Shuxin Zheng*, Guolin Ke, Di He*, Yanming Shen and Tie-Yan Liu. This repo is the official impl
Official implement of "CAT: Cross Attention in Vision Transformer".
CAT: Cross Attention in Vision Transformer This is official implement of "CAT: Cross Attention in Vision Transformer". Abstract Since Transformer has
Implementation of the "Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos" paper.
Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos Introduction Point cloud videos exhibit irregularities and lack of or
The official PyTorch implementation of recent paper - SAINT: Improved Neural Networks for Tabular Data via Row Attention and Contrastive Pre-Training
This repository is the official PyTorch implementation of SAINT. Find the paper on arxiv SAINT: Improved Neural Networks for Tabular Data via Row Atte
Unofficial PyTorch implementation of Attention Free Transformer (AFT) layers by Apple Inc.
aft-pytorch Unofficial PyTorch implementation of Attention Free Transformer's layers by Zhai, et al. [abs, pdf] from Apple Inc. Installation You can i
"SOLQ: Segmenting Objects by Learning Queries", SOLQ is an end-to-end instance segmentation framework with Transformer.
SOLQ: Segmenting Objects by Learning Queries This repository is an official implementation of the paper SOLQ: Segmenting Objects by Learning Queries.
Official codebase for Decision Transformer: Reinforcement Learning via Sequence Modeling.
Decision Transformer Lili Chen*, Kevin Lu*, Aravind Rajeswaran, Kimin Lee, Aditya Grover, Michael Laskin, Pieter Abbeel, Aravind Srinivas†, and Igor M
You Only 👀 One Sequence
You Only 👀 One Sequence TL;DR: We study the transferability of the vanilla ViT pre-trained on mid-sized ImageNet-1k to the more challenging COCO obje
MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens
MSG-Transformer Official implementation of the paper MSG-Transformer: Exchanging Local Spatial Information by Manipulating Messenger Tokens, by Jiemin
This repo contains the official code and pre-trained models for the Dynamic Vision Transformer (DVT).
Dynamic-Vision-Transformer (Pytorch) This repo contains the official code and pre-trained models for the Dynamic Vision Transformer (DVT). Not All Ima
Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).
Deep Text Search - AI Based Text Search & Recommendation System Deep Text Search is an AI-powered multilingual text search and recommendation engine w
Implementation of CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification
CrossViT : Cross-Attention Multi-Scale Vision Transformer for Image Classification This is an unofficial PyTorch implementation of CrossViT: Cross-Att
This is an official implementation for "ResT: An Efficient Transformer for Visual Recognition".
ResT By Qing-Long Zhang and Yu-Bin Yang [State Key Laboratory for Novel Software Technology at Nanjing University] This repo is the official implement
Unofficial TensorFlow implementation of the Keyword Spotting Transformer model
Keyword Spotting Transformer This is the unofficial TensorFlow implementation of the Keyword Spotting Transformer model. This model is used to train o
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch
Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)
ImageProcessingTransformer Third party Pytorch implement of Image Processing Transformer (Pre-Trained Image Processing Transformer arXiv:2012.00364v2)
PyTorch implementation of some learning rate schedulers for deep learning researcher.
pytorch-lr-scheduler PyTorch implementation of some learning rate schedulers for deep learning researcher. Usage WarmupReduceLROnPlateauScheduler Visu
TrTr: Visual Tracking with Transformer
TrTr: Visual Tracking with Transformer We propose a novel tracker network based on a powerful attention mechanism called Transformer encoder-decoder a
PyTorch code of my ICDAR 2021 paper Vision Transformer for Fast and Efficient Scene Text Recognition (ViTSTR)
Vision Transformer for Fast and Efficient Scene Text Recognition (ICDAR 2021) ViTSTR is a simple single-stage model that uses a pre-trained Vision Tra
Code for Transformer Hawkes Process, ICML 2020.
Transformer Hawkes Process Source code for Transformer Hawkes Process (ICML 2020). Run the code Dependencies Python 3.7. Anaconda contains all the req
We will release the code of "ConTNet: Why not use convolution and transformer at the same time?" in this repo
ConTNet Introduction ConTNet (Convlution-Tranformer Network) is proposed mainly in response to the following two issues: (1) ConvNets lack a large rec
Face Transformer for Recognition
Face-Transformer This is the code of Face Transformer for Recognition (https://arxiv.org/abs/2103.14803v2). Recently there has been great interests of
Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
Parallel Tacotron2 Pytorch Implementation of Google's Parallel Tacotron 2: A Non-Autoregressive Neural TTS Model with Differentiable Duration Modeling
A look-ahead multi-entity Transformer for modeling coordinated agents.
baller2vec++ This is the repository for the paper: Michael A. Alcorn and Anh Nguyen. baller2vec++: A Look-Ahead Multi-Entity Transformer For Modeling
This repository contains PyTorch code for Robust Vision Transformers.
This repository contains PyTorch code for Robust Vision Transformers.
A PaddlePaddle version image model zoo.
Paddle-Image-Models English | 简体中文 A PaddlePaddle version image model zoo. Install Package Install by pip: $ pip install ppim Install by wheel package
Unofficial implementation of MLP-Mixer: An all-MLP Architecture for Vision
MLP-Mixer: An all-MLP Architecture for Vision This repo contains PyTorch implementation of MLP-Mixer: An all-MLP Architecture for Vision. Usage : impo
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai
The code for two papers: Feedback Transformer and Expire-Span.
transformer-sequential This repo contains the code for two papers: Feedback Transformer Expire-Span The training code is structured for long sequentia
Unofficial implementation of Google's FNet: Mixing Tokens with Fourier Transforms
FNet: Mixing Tokens with Fourier Transforms Pytorch implementation of Fnet : Mixing Tokens with Fourier Transforms. Citation: @misc{leethorp2021fnet,
Segmenter - Transformer for Semantic Segmentation
Segmenter - Transformer for Semantic Segmentation
Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"
ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip
Vision Transformer for 3D medical image registration (Pytorch).
ViT-V-Net: Vision Transformer for Volumetric Medical Image Registration keywords: vision transformer, convolutional neural networks, image registratio
LeViT a Vision Transformer in ConvNet's Clothing for Faster Inference
LeViT: a Vision Transformer in ConvNet's Clothing for Faster Inference This repository contains PyTorch evaluation code, training code and pretrained
Incorporating Transformer and LSTM to Kalman Filter with EM algorithm
Deep learning based state estimation: incorporating Transformer and LSTM to Kalman Filter with EM algorithm Overview Kalman Filter requires the true p
Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"
ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip
Reformer, the efficient Transformer, in Pytorch
Reformer, the Efficient Transformer, in Pytorch This is a Pytorch implementation of Reformer https://openreview.net/pdf?id=rkgNKkHtvB It includes LSH
Google AI 2018 BERT pytorch implementation
BERT-pytorch Pytorch implementation of Google AI's 2018 BERT, with simple annotation BERT 2018 BERT: Pre-training of Deep Bidirectional Transformers f
Code release for "COTR: Correspondence Transformer for Matching Across Images"
COTR: Correspondence Transformer for Matching Across Images This repository contains the inference code for COTR. We plan to release the training code
Transparent Transformer Segmentation
Transparent Transformer Segmentation Introduction This repository contains the data and code for IJCAI 2021 paper Segmenting transparent object in the
An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models.
DeepNER An Easy-to-use, Modular and Prolongable package of deep-learning based Named Entity Recognition Models. This repository contains complex Deep
Code release for "COTR: Correspondence Transformer for Matching Across Images"
COTR: Correspondence Transformer for Matching Across Images This repository contains the inference code for COTR. We plan to release the training code
LightSeq: A High-Performance Inference Library for Sequence Processing and Generation
LightSeq is a high performance inference library for sequence processing and generation implemented in CUDA. It enables highly efficient computation of modern NLP models such as BERT, GPT2, Transformer, etc. It is therefore best useful for Machine Translation, Text Generation, Dialog, Language Modelling, and other related tasks using these models.
Multi-Scale Vision Longformer: A New Vision Transformer for High-Resolution Image Encoding
Vision Longformer This project provides the source code for the vision longformer paper. Multi-Scale Vision Longformer: A New Vision Transformer for H
Official code for "End-to-End Optimization of Scene Layout" -- including VAE, Diff Render, SPADE for colorization (CVPR 2020 Oral)
End-to-End Optimization of Scene Layout Code release for: End-to-End Optimization of Scene Layout CVPR 2020 (Oral) Project site, Bibtex For help conta
So-ViT: Mind Visual Tokens for Vision Transformer
So-ViT: Mind Visual Tokens for Vision Transformer Introduction This repository contains the source code under PyTorch framework and models trai
Official Pytorch Implementation of: "ImageNet-21K Pretraining for the Masses"(2021) paper
ImageNet-21K Pretraining for the Masses Paper | Pretrained models Official PyTorch Implementation Tal Ridnik, Emanuel Ben-Baruch, Asaf Noy, Lihi Zelni
Pytorch implementation of "Training a 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet"
Token Labeling: Training an 85.4% Top-1 Accuracy Vision Transformer with 56M Parameters on ImageNet (arxiv) This is a Pytorch implementation of our te
SiT: Self-supervised vIsion Transformer
This repository contains the official PyTorch self-supervised pretraining, finetuning, and evaluation codes for SiT (Self-supervised image Transformer).
VideoGPT: Video Generation using VQ-VAE and Transformers
VideoGPT: Video Generation using VQ-VAE and Transformers [Paper][Website][Colab][Gradio Demo] We present VideoGPT: a conceptually simple architecture
[CVPR'21] Multi-Modal Fusion Transformer for End-to-End Autonomous Driving
TransFuser This repository contains the code for the CVPR 2021 paper Multi-Modal Fusion Transformer for End-to-End Autonomous Driving. If you find our
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Sequence-to-sequence framework with a focus on Neural Machine Translation based on Apache MXNet
Implementation of Convolutional enhanced image Transformer
CeiT : Convolutional enhanced image Transformer This is an unofficial PyTorch implementation of Incorporating Convolution Designs into Visual Transfor
OpenMMLab Text Detection, Recognition and Understanding Toolbox
Introduction English | 简体中文 MMOCR is an open-source toolbox based on PyTorch and mmdetection for text detection, text recognition, and the correspondi
Implementation of Perceiver, General Perception with Iterative Attention in TensorFlow
Perceiver This Python package implements Perceiver: General Perception with Iterative Attention by Andrew Jaegle in TensorFlow. This model builds on t
I-BERT: Integer-only BERT Quantization
I-BERT: Integer-only BERT Quantization HuggingFace Implementation I-BERT is also available in the master branch of HuggingFace! Visit the following li
Code for the paper "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021)
MASTER-PyTorch PyTorch reimplementation of "MASTER: Multi-Aspect Non-local Network for Scene Text Recognition" (Pattern Recognition 2021). This projec
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Cross Transformers - Pytorch (wip) Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch Install $ pip install cross-t
This is an official implementation for "Swin Transformer: Hierarchical Vision Transformer using Shifted Windows" on Object Detection and Instance Segmentation.
Swin Transformer for Object Detection This repo contains the supported code and configuration files to reproduce object detection results of Swin Tran
A fast and easy implementation of Transformer with PyTorch.
FasySeq FasySeq is a shorthand as a Fast and easy sequential modeling toolkit. It aims to provide a seq2seq model to researchers and developers, which
Elliot is a comprehensive recommendation framework that analyzes the recommendation problem from the researcher's perspective.
Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation
《LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification》(AAAI 2021) GitHub:
LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
Tool for visualizing attention in the Transformer model (BERT, GPT-2, Albert, XLNet, RoBERTa, CTRL, etc.)
Implementation of ViViT: A Video Vision Transformer
ViViT: A Video Vision Transformer Unofficial implementation of ViViT: A Video Vision Transformer. Notes: This is in WIP. Model 2 is implemented, Model
《DeepViT: Towards Deeper Vision Transformer》(2021)
DeepViT This repo is the official implementation of "DeepViT: Towards Deeper Vision Transformer". The repo is based on the timm library (https://githu
Code for the Convolutional Vision Transformer (ConViT)
ConViT : Vision Transformers with Convolutional Inductive Biases This repository contains PyTorch code for ConViT. It builds on code from the Data-Eff
Transformer related optimization, including BERT, GPT
This repository provides a script and recipe to run the highly optimized transformer-based encoder and decoder component, and it is tested and maintained by NVIDIA.
Code to reproduce the experiments in the paper "Transformer Based Multi-Source Domain Adaptation" (EMNLP 2020)
Transformer Based Multi-Source Domain Adaptation Dustin Wright and Isabelle Augenstein To appear in EMNLP 2020. Read the preprint: https://arxiv.org/a
Official PyTorch implementation for Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers, a novel method to visualize any Transformer-based network. Including examples for DETR, VQA.
PyTorch Implementation of Generic Attention-model Explainability for Interpreting Bi-Modal and Encoder-Decoder Transformers 1 Using Colab Please notic
Learning Spatio-Temporal Transformer for Visual Tracking
STARK The official implementation of the paper Learning Spatio-Temporal Transformer for Visual Tracking Hiring research interns for visual transformer
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).
TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra