1395 Repositories
Python Sign-Segmentation-with-Transformers Libraries
PyTorch impelementations of BERT-based Spelling Error Correction Models
PyTorch impelementations of BERT-based Spelling Error Correction Models
PyTorch impelementations of BERT-based Spelling Error Correction Models.
PyTorch impelementations of BERT-based Spelling Error Correction Models. 基于BERT的文本纠错模型,使用PyTorch实现。
Complete U-net Implementation with keras
U Net Lowered with Keras Complete U-net Implementation with keras Original Paper Link : https://arxiv.org/abs/1505.04597 Special Implementations : The
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
This repo is a PyTorch implementation for Paper "Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds"
Unsupervised Learning for Cuboid Shape Abstraction via Joint Segmentation from Point Clouds This repository is a PyTorch implementation for paper: Uns
(CVPR2021) DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation
DANNet: A One-Stage Domain Adaptation Network for Unsupervised Nighttime Semantic Segmentation CVPR2021(oral) [arxiv] Requirements python3.7 pytorch==
AllenNLP integration for Shiba: Japanese CANINE model
Allennlp Integration for Shiba allennlp-shiab-model is a Python library that provides AllenNLP integration for shiba-model. SHIBA is an approximate re
LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021
LoFTR-with-train-script LoFTR:Detector-Free Local Feature Matching with Transformers CVPR 2021 (with train script --- unofficial ---). About Megadepth
BRepNet: A topological message passing system for solid models
BRepNet: A topological message passing system for solid models This repository contains the an implementation of BRepNet: A topological message passin
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021]
Robust Instance Segmentation through Reasoning about Multi-Object Occlusion [CVPR 2021] Abstract Analyzing complex scenes with DNN is a challenging ta
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in clustering (CVPR2021)
PiCIE: Unsupervised Semantic Segmentation using Invariance and Equivariance in Clustering Jang Hyun Cho1, Utkarsh Mall2, Kavita Bala2, Bharath Harihar
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
Code for the paper One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation, CVPR 2021.
One Thing One Click One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation (CVPR2021) Code for the paper One Thi
LETR: Line Segment Detection Using Transformers without Edges
LETR: Line Segment Detection Using Transformers without Edges Introduction This repository contains the official code and pretrained models for Line S
The project is an official implementation of our paper "3D Human Pose Estimation with Spatial and Temporal Transformers".
3D Human Pose Estimation with Spatial and Temporal Transformers This repo is the official implementation for 3D Human Pose Estimation with Spatial and
OrienMask: Real-time Instance Segmentation with Discriminative Orientation Maps
OrienMask This repository implements the framework OrienMask for real-time instance segmentation. It achieves 34.8 mask AP on COCO test-dev at the spe
Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN
Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN If you use this code for your research, please cite ou
This repository contains the code for our fast polygonal building extraction from overhead images pipeline.
Polygonal Building Segmentation by Frame Field Learning We add a frame field output to an image segmentation neural network to improve segmentation qu
PyTorch evaluation code for Delving Deep into the Generalization of Vision Transformers under Distribution Shifts.
Out-of-distribution Generalization Investigation on Vision Transformers This repository contains PyTorch evaluation code for Delving Deep into the Gen
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
easySpeech is an open-source Python wrapper for google speech to text API that doesn't require PyAudio(So you especially windows user don't have to deal with the errors while installing PyAudio) and also works with hugging face transformers
easySpeech easySpeech is an open source python wrapper for google speech to text api that doesn't require PyAaudio(So you specially windows user don't
Code for Towards Streaming Perception (ECCV 2020) :car:
sAP — Code for Towards Streaming Perception ECCV Best Paper Honorable Mention Award Feb 2021: Announcing the Streaming Perception Challenge (CVPR 2021
An interpreter for RASP as described in the ICML 2021 paper "Thinking Like Transformers"
RASP Setup Mac or Linux Run ./setup.sh . It will create a python3 virtual environment and install the dependencies for RASP. It will also try to insta
2021海华AI挑战赛·中文阅读理解·技术组·第三名
文字是人类用以记录和表达的最基本工具,也是信息传播的重要媒介。透过文字与符号,我们可以追寻人类文明的起源,可以传播知识与经验,读懂文字是认识与了解的第一步。对于人工智能而言,它的核心问题之一就是认知,而认知的核心则是语义理解。
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
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
Code + pre-trained models for the paper Keeping Your Eye on the Ball Trajectory Attention in Video Transformers
Motionformer This is an official pytorch implementation of paper Keeping Your Eye on the Ball: Trajectory Attention in Video Transformers. In this rep
FANet - Real-time Semantic Segmentation with Fast Attention
FANet Real-time Semantic Segmentation with Fast Attention Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko , Stan Sc
Code for weakly supervised segmentation of a single class
SingleClassRL Implementation of weak single object segmentation from paper "Regularized Loss for Weakly Supervised Single Class Semantic Segmentation"
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation (CVPR 2021)
ASGNet The code is for the paper "Adaptive Prototype Learning and Allocation for Few-Shot Segmentation" (accepted to CVPR 2021) [arxiv] Overview data/
Aerial Imagery dataset for fire detection: classification and segmentation (Unmanned Aerial Vehicle (UAV))
Aerial Imagery dataset for fire detection: classification and segmentation using Unmanned Aerial Vehicle (UAV) Title FLAME (Fire Luminosity Airborne-b
Load What You Need: Smaller Multilingual Transformers for Pytorch and TensorFlow 2.0.
Smaller Multilingual Transformers This repository shares smaller versions of multilingual transformers that keep the same representations offered by t
Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch
Segformer - Pytorch Implementation of Segformer, Attention + MLP neural network for segmentation, in Pytorch. Install $ pip install segformer-pytorch
Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation
STCN Rethinking Space-Time Networks with Improved Memory Coverage for Efficient Video Object Segmentation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [a
Official repository for "On Improving Adversarial Transferability of Vision Transformers" (2021)
Improving-Adversarial-Transferability-of-Vision-Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Fahad Khan, Fatih Porikli arxiv link A
Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers.
Less is More: Pay Less Attention in Vision Transformers Official PyTorch implementation of Less is More: Pay Less Attention in Vision Transformers. By
CATs: Semantic Correspondence with Transformers
CATs: Semantic Correspondence with Transformers For more information, check out the paper on [arXiv]. Training with different backbones and evaluation
Self-Attention Between Datapoints: Going Beyond Individual Input-Output Pairs in Deep Learning
We challenge a common assumption underlying most supervised deep learning: that a model makes a prediction depending only on its parameters and the features of a single input. To this end, we introduce a general-purpose deep learning architecture that takes as input the entire dataset instead of processing one datapoint at a time.
"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.
This is the official Pytorch implementation of "Lung Segmentation from Chest X-rays using Variational Data Imputation", Raghavendra Selvan et al. 2020
README This is the official Pytorch implementation of "Lung Segmentation from Chest X-rays using Variational Data Imputation", Raghavendra Selvan et a
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification
DynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification Created by Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, Ch
The implementation of PEMP in paper "Prior-Enhanced Few-Shot Segmentation with Meta-Prototypes"
Prior-Enhanced network with Meta-Prototypes (PEMP) This is the PyTorch implementation of PEMP. Overview of PEMP Meta-Prototypes & Adaptive Prototypes
Official repository for "Intriguing Properties of Vision Transformers" (2021)
Intriguing Properties of Vision Transformers Muzammal Naseer, Kanchana Ranasinghe, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, & Ming-Hsuan Yang P
Official repository for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'21, Oral Presentation)
Official PyTorch Implementation for HOTR: End-to-End Human-Object Interaction Detection with Transformers (CVPR'2021, Oral Presentation) HOTR: End-to-
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
[CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision
TorchSemiSeg [CVPR 2021] Semi-Supervised Semantic Segmentation with Cross Pseudo Supervision by Xiaokang Chen1, Yuhui Yuan2, Gang Zeng1, Jingdong Wang
The toolkit to generate auto labeled datasets
Ozeu Ozeu is the toolkit to autolabal dataset for instance segmentation. You can generate datasets labaled with segmentation mask and bounding box fro
simpleT5 is built on top of PyTorch-lightning⚡️ and Transformers🤗 that lets you quickly train your T5 models.
Quickly train T5 models in just 3 lines of code + ONNX support simpleT5 is built on top of PyTorch-lightning ⚡️ and Transformers 🤗 that lets you quic
PyTorch implementation of: Michieli U. and Zanuttigh P., "Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations", CVPR 2021.
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations This is the official PyTorch implementation
A PyTorch implementation of EfficientDet.
A PyTorch impl of EfficientDet faithful to the original Google impl w/ ported weights
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
(AAAI2020)Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing
Grapy-ML: Graph Pyramid Mutual Learning for Cross-dataset Human Parsing This repository contains pytorch source code for AAAI2020 oral paper: Grapy-ML
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
This is an official implementation of CvT: Introducing Convolutions to Vision Transformers.
Introduction This is an official implementation of CvT: Introducing Convolutions to Vision Transformers. We present a new architecture, named Convolut
Research code for CVPR 2021 paper "End-to-End Human Pose and Mesh Reconstruction with Transformers"
MeshTransformer ✨ This is our research code of End-to-End Human Pose and Mesh Reconstruction with Transformers. MEsh TRansfOrmer is a simple yet effec
Medical Image Segmentation using Squeeze-and-Expansion Transformers
Medical Image Segmentation using Squeeze-and-Expansion Transformers Introduction This repository contains the code of the IJCAI'2021 paper 'Medical Im
Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving
SalsaNext: Fast, Uncertainty-aware Semantic Segmentation of LiDAR Point Clouds for Autonomous Driving Abstract In this paper, we introduce SalsaNext f
Pytorch codes for "Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation"
Self-Supervised-MVS This repository is the official PyTorch implementation of our AAAI 2021 paper: "Self-supervised Multi-view Stereo via Effective Co
code for `Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation`
Look Closer to Segment Better: Boundary Patch Refinement for Instance Segmentation (CVPR 2021) Introduction PBR is a conceptually simple yet effective
precise iris segmentation
PI-DECODER Introduction PI-DECODER, a decoder structure designed for Precise Iris Segmentation and Location. The decoder structure is shown below: Ple
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CVPR 2021)
Semi-supervised Semantic Segmentation with Directional Context-aware Consistency (CAC) Xin Lai*, Zhuotao Tian*, Li Jiang, Shu Liu, Hengshuang Zhao, Li
This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.
LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian
Pytorch code for ICRA'21 paper: "Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation"
Hierarchical Cross-Modal Agent for Robotics Vision-and-Language Navigation This repository is the pytorch implementation of our paper: Hierarchical Cr
[ECCV 2020] Gradient-Induced Co-Saliency Detection
Gradient-Induced Co-Saliency Detection Zhao Zhang*, Wenda Jin*, Jun Xu, Ming-Ming Cheng ⭐ Project Home » The official repo of the ECCV 2020 paper Grad
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"
When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models
Finding an Unsupervised Image Segmenter in each of your Deep Generative Models Description Recent research has shown that numerous human-interpretable
[CVPR 2021] Exemplar-Based Open-Set Panoptic Segmentation Network (EOPSN)
EOPSN: Exemplar-Based Open-Set Panoptic Segmentation Network (CVPR 2021) PyTorch implementation for EOPSN. We propose open-set panoptic segmentation t
Contains code for the paper "Vision Transformers are Robust Learners".
Vision Transformers are Robust Learners This repository contains the code for the paper Vision Transformers are Robust Learners by Sayak Paul* and Pin
Lipstick ain't enough: Beyond Color-Matching for In-the-Wild Makeup Transfer (CVPR 2021)
Table of Content Introduction Datasets Getting Started Requirements Usage Example Training & Evaluation CPM: Color-Pattern Makeup Transfer CPM is a ho
Train 🤗transformers with DeepSpeed: ZeRO-2, ZeRO-3
Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.
Application that instantly translates sign-language to letters.
Sign Language Translator Project Description The main purpose of project is translating sign-language to letters. In accordance with this purpose we d
XtremeDistil framework for distilling/compressing massive multilingual neural network models to tiny and efficient models for AI at scale
XtremeDistilTransformers for Distilling Massive Multilingual Neural Networks ACL 2020 Microsoft Research [Paper] [Video] Releasing [XtremeDistilTransf
Code for Referring Image Segmentation via Cross-Modal Progressive Comprehension, CVPR2020.
CMPC-Refseg Code of our CVPR 2020 paper Referring Image Segmentation via Cross-Modal Progressive Comprehension. Shaofei Huang*, Tianrui Hui*, Si Liu,
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
Implementation of gMLP, an all-MLP replacement for Transformers, in Pytorch
This repository contains PyTorch code for Robust Vision Transformers.
This repository contains PyTorch code for Robust Vision Transformers.
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation This project hosts the code for implementing the DCT-MASK algorithms
Segmenter - Transformer for Semantic Segmentation
Segmenter - Transformer for Semantic Segmentation
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation (CVPR 2021)
Self-supervised Augmentation Consistency for Adapting Semantic Segmentation This repository contains the official implementation of our paper: Self-su
QueryInst: Parallelly Supervised Mask Query for Instance Segmentation
QueryInst is a simple and effective query based instance segmentation method driven by parallel supervision on dynamic mask heads, which outperforms previous arts in terms of both accuracy and speed.
TrackFormer: Multi-Object Tracking with Transformers
TrackFormer: Multi-Object Tracking with Transformers This repository provides the official implementation of the TrackFormer: Multi-Object Tracking wi
Exploring whether attention is necessary for vision transformers
Do You Even Need Attention? A Stack of Feed-Forward Layers Does Surprisingly Well on ImageNet Paper/Report TL;DR We replace the attention layer in a v
Code for our paper Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation
CorDA Code for our paper Domain Adaptive Semantic Segmentation with Self-Supervised Depth Estimation Prerequisite Please create and activate the follo
code for CVPR paper Zero-shot Instance Segmentation
Code for CVPR2021 paper Zero-shot Instance Segmentation Code requirements python: python3.7 nvidia GPU pytorch1.1.0 GCC =5.4 NCCL 2 the other python
Auto Seg-Loss: Searching Metric Surrogates for Semantic Segmentation
Auto-Seg-Loss By Hao Li, Chenxin Tao, Xizhou Zhu, Xiaogang Wang, Gao Huang, Jifeng Dai This is the official implementation of the ICLR 2021 paper Auto
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
jiant is an NLP toolkit
jiant is an NLP toolkit The multitask and transfer learning toolkit for natural language processing research Why should I use jiant? jiant supports mu
keras implement of transformers for humans
keras implement of transformers for humans
An easier way to build neural search on the cloud
Jina is geared towards building search systems for any kind of data, including text, images, audio, video and many more. With the modular design & multi-layer abstraction, you can leverage the efficient patterns to build the system by parts, or chaining them into a Flow for an end-to-end experience.
Transparent Transformer Segmentation
Transparent Transformer Segmentation Introduction This repository contains the data and code for IJCAI 2021 paper Segmenting transparent object in the
(IEEE TIP 2021) Regularized Densely-connected Pyramid Network for Salient Instance Segmentation
RDPNet IEEE TIP 2021: Regularized Densely-connected Pyramid Network for Salient Instance Segmentation PyTorch training and testing code are available.
ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)
This is the project page for the paper: ISTR: End-to-End Instance Segmentation via Transformers, Jie Hu, Liujuan Cao, Yao Lu, ShengChuan Zhang, Yan Wa
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation (CVPR 2021)
Anti-Adversarially Manipulated Attributions for Weakly and Semi-Supervised Semantic Segmentation Input Image Initial CAM Successive Maps with adversar
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
Self-Supervised Vision Transformers with DINO PyTorch implementation and pretrained models for DINO. For details, see Emerging Properties in Self-Supe
Geometry-Free View Synthesis: Transformers and no 3D Priors
Geometry-Free View Synthesis: Transformers and no 3D Priors Geometry-Free View Synthesis: Transformers and no 3D Priors Robin Rombach*, Patrick Esser*
Location-Sensitive Visual Recognition with Cross-IOU Loss
The trained models are temporarily unavailable, but you can train the code using reasonable computational resource. Location-Sensitive Visual Recognit
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation
Discriminative Region Suppression for Weakly-Supervised Semantic Segmentation (AAAI 2021) Official pytorch implementation of our paper: Discriminative
Implementation of "Efficient Regional Memory Network for Video Object Segmentation" (Xie et al., CVPR 2021).
RMNet This repository contains the source code for the paper Efficient Regional Memory Network for Video Object Segmentation. Cite this work @inprocee
[CVPR 2021] MiVOS - Mask Propagation module. Reproduced STM (and better) with training code :star2:. Semi-supervised video object segmentation evaluation.
MiVOS (CVPR 2021) - Mask Propagation Ho Kei Cheng, Yu-Wing Tai, Chi-Keung Tang [arXiv] [Paper PDF] [Project Page] [Papers with Code] This repo impleme