3727 Repositories
Python semantic-segmentation-pytorch Libraries
PyTorch-lightning implementation of the ESFW module proposed in our paper Edge-Selective Feature Weaving for Point Cloud Matching
Edge-Selective Feature Weaving for Point Cloud Matching This repository contains a PyTorch-lightning implementation of the ESFW module proposed in our
Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch
C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ
KoRean based ELECTRA pre-trained models (KR-ELECTRA) for Tensorflow and PyTorch
KoRean based ELECTRA (KR-ELECTRA) This is a release of a Korean-specific ELECTRA model with comparable or better performances developed by the Computa
PyTorch implementation for NCL (Neighborhood-enrighed Contrastive Learning)
NCL (Neighborhood-enrighed Contrastive Learning) This is the official PyTorch implementation for the paper: Zihan Lin*, Changxin Tian*, Yupeng Hou* Wa
A pure PyTorch batched computation implementation of "CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition"
A pure PyTorch batched computation implementation of "CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition"
A lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look At CoefficienTs)
Real-time Instance Segmentation and Lane Detection This is a lane detection integrated Real-time Instance Segmentation based on YOLACT (You Only Look
FNet Implementation with TensorFlow & PyTorch
FNet Implementation with TensorFlow & PyTorch. TensorFlow & PyTorch implementation of the paper "FNet: Mixing Tokens with Fourier Transforms". Overvie
Image-to-image regression with uncertainty quantification in PyTorch
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
Learning Visual Words for Weakly-Supervised Semantic Segmentation
[IJCAI 2021] Learning Visual Words for Weakly-Supervised Semantic Segmentation Implementation of IJCAI 2021 paper Learning Visual Words for Weakly-Sup
PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation
PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation
Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection
DDMP-3D Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021. Instroduction T
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection?
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
PyTorch implementations of the NeRF model described in "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis"
PyTorch NeRF and pixelNeRF NeRF: Tiny NeRF: pixelNeRF: This repository contains minimal PyTorch implementations of the NeRF model described in "NeRF:
SGPT: Multi-billion parameter models for semantic search
SGPT: Multi-billion parameter models for semantic search This repository contains code, results and pre-trained models for the paper SGPT: Multi-billi
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning"
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning".
Neural Radiance Fields Using PyTorch
This project is a PyTorch implementation of Neural Radiance Fields (NeRF) for reproduction of results whilst running at a faster speed.
Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated
Create a semantic search engine with a neural network (i.e. BERT) whose knowledge base can be updated. This engine can later be used for downstream tasks in NLP such as Q&A, summarization, generation, and natural language understanding (NLU).
KinectFusion implemented in Python with PyTorch
KinectFusion implemented in Python with PyTorch This is a lightweight Python implementation of KinectFusion. All the core functions (TSDF volume, fram
Rank-One Model Editing for Locating and Editing Factual Knowledge in GPT
Rank-One Model Editing (ROME) This repository provides an implementation of Rank-One Model Editing (ROME) on auto-regressive transformers (GPU-only).
PyTorch implementation of SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I
NeuroGen: activation optimized image synthesis for discovery neuroscience
NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation
Multi-atlas segmentation (MAS) is a promising framework for medical image segmentation. Generally, MAS methods register multiple atlases, i.e., medical images with corresponding labels, to a target image;
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training
Official code of Retinal Vessel Segmentation with Pixel-wise Adaptive Filters and Consistency Training (ISBI 2022)
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg
Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates"
Peer Loss functions This repository is the (Multi-Class & Deep Learning) Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels wi
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption
⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation
DCSAU-Net: A Deeper and More Compact Split-Attention U-Net for Medical Image Segmentation By Qing Xu, Wenting Duan and Na He Requirements pytorch==1.1
PyTorch implementation of the paper: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Estimate the noise transition matrix with f-mutual information. This co
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"
Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive Selective Coding)
HCSC: Hierarchical Contrastive Selective Coding This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.
RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection"
Official code for paper "ISNet: Costless and Implicit Image Segmentation for Deep Classifiers, with Application in COVID-19 Detection". LRPDenseNet.py
Pytorch Implementation for Dilated Continuous Random Field
DilatedCRF Pytorch implementation for fully-learnable DilatedCRF. If you find my work helpful, please consider our paper: @article{Mo2022dilatedcrf,
Pytorch implementation of TailCalibX : Feature Generation for Long-tail Classification
TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [
ElasticFace: Elastic Margin Loss for Deep Face Recognition
This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap
Official PyTorch implementation of the NeurIPS 2021 paper StyleGAN3
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)"
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that generalizes score-based models to fully nonlinear forward and backward diffusions.
This repository provides an efficient PyTorch-based library for training deep models.
An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make
Build upon neural radiance fields to create a scene-specific implicit 3D semantic representation, Semantic-NeRF
Semantic-NeRF: Semantic Neural Radiance Fields Project Page | Video | Paper | Data In-Place Scene Labelling and Understanding with Implicit Scene Repr
This code is the implementation of Text Emotion Recognition (TER) with linguistic features
APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions
APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
Tensorflow2 Keras-based Semantic Segmentation Models Implementation
NeuralForecast is a Python library for time series forecasting with deep learning models
NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.
Customers Segmentation with RFM Scores and K-means
Customer Segmentation with RFM Scores and K-means RFM Segmentation table: K-Means Clustering: Business Problem Rule-based customer segmentation machin
CT Based COVID 19 Diagnose by Image Processing and Deep Learning
This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.
A pure PyTorch implementation of the loss described in "Online Segment to Segment Neural Transduction"
ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t
FishNet: One Stage to Detect, Segmentation and Pose Estimation
FishNet FishNet: One Stage to Detect, Segmentation and Pose Estimation Introduction In this project, we combine target detection, instance segmentatio
Sequence-tagging using deep learning
Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface
A simple tutoral for error correction task, based on Pytorch
gramcorrector A simple tutoral for error correction task, based on Pytorch Grammatical Error Detection (sentence-level) a binary sequence-based classi
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
A U-Net combined with a variational auto-encoder that is able to learn conditional distributions over semantic segmentations.
Probabilistic U-Net + **Update** + An improved Model (the Hierarchical Probabilistic U-Net) + LIDC crops is now available. See below. Re-implementatio
CCP dataset from Clothing Co-Parsing by Joint Image Segmentation and Labeling
Clothing Co-Parsing (CCP) Dataset Clothing Co-Parsing (CCP) dataset is a new clothing database including elaborately annotated clothing items. 2, 098
Official PyTorch implementation of StyleGAN3
Modified StyleGAN3 Repo Changes Made tied to python 3.7 syntax .jpgs instead of .pngs for training sample seeds to recreate the 1024 training grid wit
Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.
pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D
YOLOv7 - Framework Beyond Detection
🔥🔥🔥🔥 YOLO with Transformers and Instance Segmentation, with TensorRT acceleration! 🔥🔥🔥
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
A PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detection.
R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect
Torch-mutable-modules - Use in-place and assignment operations on PyTorch module parameters with support for autograd
Torch Mutable Modules Use in-place and assignment operations on PyTorch module p
Pytorch implementation of OCNet series and SegFix.
openseg.pytorch News 2021/09/14 MMSegmentation has supported our ISANet and refer to ISANet for more details. 2021/08/13 We have released the implemen
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Semantic Segmentation Suite in TensorFlow
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Image Segmentation and Object Detection in Pytorch
Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report
This project aims at providing a concise, easy-to-use, modifiable reference implementation for semantic segmentation models using PyTorch.
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
Javascript image annotation tool based on image segmentation.
JS Segment Annotator Javascript image annotation tool based on image segmentation. Label image regions with mouse. Written in vanilla Javascript, with
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
SAAVN - Sound Adversarial Audio-Visual Navigation,ICLR2022 (In PyTorch)
SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC
Thresholding-and-masking-using-OpenCV - Image Thresholding is used for image segmentation
Image Thresholding is used for image segmentation. From a grayscale image, thresholding can be used to create binary images. In thresholding we pick a threshold T.
Pytorch implementation of various High Dynamic Range (HDR) Imaging algorithms
Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme
Sematic-Segmantation - Semantic Segmentation on MIT ADE20K dataset in PyTorch
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch impleme
Mae segmentation - Reproduction of semantic segmentation using masked autoencoder (mae)
ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation
Real-time domain adaptation for semantic segmentation
Advanced-Machine-Learning This repository contains the code for the project Real
Implementing DropPath/StochasticDepth in PyTorch
%load_ext memory_profiler Implementing Stochastic Depth/Drop Path In PyTorch DropPath is available on glasses my computer vision library! Introduction
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"
Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound
PyTorch implementation of DirectCLR from paper Understanding Dimensional Collapse in Contrastive Self-supervised Learning
DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It
The code uses SegFormer for Semantic Segmentation on Drone Dataset.
SegFormer_Segmentation The code uses SegFormer for Semantic Segmentation on Drone Dataset. The details for the SegFormer can be obtained from the foll
Cossim - Sharpened Cosine Distance implementation in PyTorch
Sharpened Cosine Distance PyTorch implementation of the Sharpened Cosine Distanc
Constrained Language Models Yield Few-Shot Semantic Parsers
Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap
traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation toolbox based on PyTorch.
traiNNer traiNNer is an open source image and video restoration (super-resolution, denoising, deblurring and others) and image to image translation to
Decorators for maximizing memory utilization with PyTorch & CUDA
torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and
PyTorch code for BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
LogAvgExp - Pytorch Implementation of LogAvgExp
LogAvgExp - Pytorch Implementation of LogAvgExp for Pytorch Install $ pip instal
Code for You Only Cut Once: Boosting Data Augmentation with a Single Cut
You Only Cut Once (YOCO) YOCO is a simple method/strategy of performing augmenta
Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation
SSWS-loss_function_based_on_MS-TCN Supervised Sliding Window Smoothing Loss Function Based on MS-TCN for Video Segmentation Supervised Sliding Window
An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax
Simple Transformer An implementation of the "Attention is all you need" paper without extra bells and whistles, or difficult syntax. Note: The only ex
Template repository for managing machine learning research projects built with PyTorch-Lightning
Tutorial Repository with a minimal example for showing how to deploy training across various compute infrastructure.
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines
spaCy-wrap: For Wrapping fine-tuned transformers in spaCy pipelines spaCy-wrap is minimal library intended for wrapping fine-tuned transformers from t
Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper
Continual Learning With Filter Atom Swapping Pytorch Implementation of Continual Learning With Filter Atom Swapping (ICLR'22 Spolight) Paper If find t
DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation
DFFNet Paper DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation. Xiangyan Tang, Wenxuan Tu, Keqiu Li, J
Pytorch Performace Tuning, WandB, AMP, Multi-GPU, TensorRT, Triton
Plant Pathology 2020 FGVC7 Introduction A deep learning model pipeline for training, experimentaiton and deployment for the Kaggle Competition, Plant
This is the source code of the 1st place solution for segmentation task (with Dice 90.32%) in 2021 CCF BDCI challenge.
1st place solution in CCF BDCI 2021 ULSEG challenge This is the source code of the 1st place solution for ultrasound image angioma segmentation task (
RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and rearranging captions and pictures. Unlike other versions of the model we use BERT for text encoder and SWIN transformer for image encoder.
ruCLIP-SB RuCLIP-SB (Russian Contrastive Language–Image Pretraining SWIN-BERT) is a multimodal model for obtaining images and text similarities and re
My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs (GNN, GAT, GraphSAGE, GCN)
machine-learning-with-graphs My solutions for Stanford University course CS224W: Machine Learning with Graphs Fall 2021 colabs Course materials can be
Computer Vision Paper Reviews with Key Summary of paper, End to End Code Practice and Jupyter Notebook converted papers
Computer-Vision-Paper-Reviews Computer Vision Paper Reviews with Key Summary along Papers & Codes. Jonathan Choi 2021 The repository provides 100+ Pap