2751 Repositories
Python deep-clustering Libraries
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
🚪✊Knock Knock: Get notified when your training ends with only two additional lines of code
Knock Knock A small library to get a notification when your training is complete or when it crashes during the process with two additional lines of co
Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects
Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Gated-Shape CNN for Semantic Segmentation (ICCV 2019)
GSCNN This is the official code for: Gated-SCNN: Gated Shape CNNs for Semantic Segmentation Towaki Takikawa, David Acuna, Varun Jampani, Sanja Fidler
A CV toolkit for my papers.
PyTorch-Encoding created by Hang Zhang Documentation Please visit the Docs for detail instructions of installation and usage. Please visit the link to
reimpliment of DFANet: Deep Feature Aggregation for Real-Time Semantic Segmentation
DFANet This repo is an unofficial pytorch implementation of DFANet:Deep Feature Aggregation for Real-Time Semantic Segmentation log 2019.4.16 After 48
Code for our paper "Multi-scale Guided Attention for Medical Image Segmentation"
Medical Image Segmentation with Guided Attention This repository contains the code of our paper: "'Multi-scale self-guided attention for medical image
UPSNet: A Unified Panoptic Segmentation Network
UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te
Understanding Convolution for Semantic Segmentation
TuSimple-DUC by Panqu Wang, Pengfei Chen, Ye Yuan, Ding Liu, Zehua Huang, Xiaodi Hou, and Garrison Cottrell. Introduction This repository is for Under
Learning to Adapt Structured Output Space for Semantic Segmentation, CVPR 2018 (spotlight)
Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s
Tensorflow Implementation of Pixel Transposed Convolutional Networks (PixelTCN and PixelTCL)
Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel
Real-time Joint Semantic Reasoning for Autonomous Driving
MultiNet MultiNet is able to jointly perform road segmentation, car detection and street classification. The model achieves real-time speed and state-
PSPNet in Chainer
PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Multipath RefineNet A MATLAB based framework for semantic image segmentation and general dense prediction tasks on images. This is the source code for
Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images
Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K
The repository contains source code and models to use PixelNet architecture used for various pixel-level tasks. More details can be accessed at http://www.cs.cmu.edu/~aayushb/pixelNet/.
PixelNet: Representation of the pixels, by the pixels, and for the pixels. We explore design principles for general pixel-level prediction problems, f
TensorFlow implementation of ENet
TensorFlow-ENet TensorFlow implementation of ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. This model was tested on th
TensorFlow implementation of ENet, trained on the Cityscapes dataset.
segmentation TensorFlow implementation of ENet (https://arxiv.org/pdf/1606.02147.pdf) based on the official Torch implementation (https://github.com/e
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation.
ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too
ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation
ENet in Caffe Execution times and hardware requirements Network 1024x512 1280x720 Parameters Model size (fp32) ENet 20.4 ms 32.9 ms 0.36 M 1.5 MB SegN
Fully convolutional networks for semantic segmentation
FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo
Pytorch for Segmentation
Pytorch for Semantic Segmentation This repo has been deprecated currently and I will not maintain it. Meanwhile, I strongly recommend you can refer to
Chainer Implementation of Fully Convolutional Networks. (Training code to reproduce the original result is available.)
fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as
FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation
FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision
TorchCV: A PyTorch-Based Framework for Deep Learning in Computer Vision @misc{you2019torchcv, author = {Ansheng You and Xiangtai Li and Zhen Zhu a
DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe.
DeepLab Introduction DeepLab is a state-of-art deep learning system for semantic image segmentation built on top of Caffe. It combines densely-compute
SegNet-like Autoencoders in TensorFlow
SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a
A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation
Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15
Implementation of SegNet: A Deep Convolutional Encoder-Decoder Architecture for Semantic Pixel-Wise Labelling
Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A
Semantic segmentation models, datasets and losses implemented in PyTorch.
Semantic Segmentation in PyTorch Semantic Segmentation in PyTorch Requirements Main Features Models Datasets Losses Learning rate schedulers Data augm
Real-Time Semantic Segmentation in Mobile device
Real-Time Semantic Segmentation in Mobile device This project is an example project of semantic segmentation for mobile real-time app. The architectur
Generic U-Net Tensorflow implementation for image segmentation
Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu
U-Net: Convolutional Networks for Biomedical Image Segmentation
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras
Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne
A combination of autoregressors and autoencoders using XLNet for sentiment analysis
A combination of autoregressors and autoencoders using XLNet for sentiment analysis Abstract In this paper sentiment analysis has been performed in or
Models Supported: AlbUNet [18, 34, 50, 101, 152] (1D and 2D versions for Single and Multiclass Segmentation, Feature Extraction with supports for Deep Supervision and Guided Attention)
AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed
Transformers and related deep network architectures are summarized and implemented here.
Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct
Python based framework for Automatic AI for Regression and Classification over numerical data.
Python based framework for Automatic AI for Regression and Classification over numerical data. Performs model search, hyper-parameter tuning, and high-quality Jupyter Notebook code generation.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
A criticism of a recent paper on buggy image downsampling methods in popular image processing and deep learning libraries.
Interactive convnet features visualization for Keras
Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis
Keyword-BERT: Keyword-Attentive Deep Semantic Matching
project discription An implementation of the Keyword-BERT model mentioned in my paper Keyword-Attentive Deep Semantic Matching (Plz cite this github r
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
Predict the latency time of the deep learning models
Deep Neural Network Prediction Step 1. Genernate random parameters and Run them sequentially : $ python3 collect_data.py -gp -ep -pp -pl pooling -num
Yolov5 + Deep Sort with PyTorch
딥소트 수정중 Yolov5 + Deep Sort with PyTorch Introduction This repository contains a two-stage-tracker. The detections generated by YOLOv5, a family of obj
Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE
SMU A Tensorflow Implementation of SMU: SMOOTH ACTIVATION FUNCTION FOR DEEP NETWORKS USING SMOOTHING MAXIMUM TECHNIQUE arXiv https://arxiv.org/abs/211
Implementation of the bachelor's thesis "Real-time stock predictions with deep learning and news scraping".
Real-time stock predictions with deep learning and news scraping This repository contains a partial implementation of my bachelor's thesis "Real-time
An offline deep reinforcement learning library
d3rlpy: An offline deep reinforcement learning library d3rlpy is an offline deep reinforcement learning library for practitioners and researchers. imp
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech
Meta-TTS: Meta-Learning for Few-shot SpeakerAdaptive Text-to-Speech This repository is the official implementation of "Meta-TTS: Meta-Learning for Few
The official implementation of Theme Transformer
Theme Transformer This is the official implementation of Theme Transformer. Checkout our demo and paper : Demo | arXiv Environment: using python versi
Laser device for neutralizing - mosquitoes, weeds and pests
Laser device for neutralizing - mosquitoes, weeds and pests (in progress) Here I will post information for creating a laser device. A warning!! How It
Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.
Homepage | Paper | Datasets | Leaderboard | Documentation Graph Robustness Benchmark (GRB) provides scalable, unified, modular, and reproducible evalu
[NeurIPS'20] Multiscale Deep Equilibrium Models
Multiscale Deep Equilibrium Models 💥 💥 💥 💥 This repo is deprecated and we will soon stop actively maintaining it, as a more up-to-date (and simple
My implementation of Image Inpainting - A deep learning Inpainting model
Image Inpainting What is Image Inpainting Image inpainting is a restorative process that allows for the fixing or removal of unwanted parts within ima
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
Classification of EEG data using Deep Learning
Graduation-Project Classification of EEG data using Deep Learning Epilepsy is the most common neurological disease in the world. Epilepsy occurs as a
Implementation of Hourglass Transformer, in Pytorch, from Google and OpenAI
Hourglass Transformer - Pytorch (wip) Implementation of Hourglass Transformer, in Pytorch. It will also contain some of my own ideas about how to make
A collection of differentiable SVD methods and also the official implementation of the ICCV21 paper "Why Approximate Matrix Square Root Outperforms Accurate SVD in Global Covariance Pooling?"
Differentiable SVD Introduction This repository contains: The official Pytorch implementation of ICCV21 paper Why Approximate Matrix Square Root Outpe
[ICCV'21] Pri3D: Can 3D Priors Help 2D Representation Learning?
Pri3D: Can 3D Priors Help 2D Representation Learning? [ICCV 2021] Pri3D leverages 3D priors for downstream 2D image understanding tasks: during pre-tr
RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth, in ICCV 2021 (oral)
RINDNet RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth Mengyang Pu, Yaping Huang, Qingji Guan and Haibin Lin
[ICCV2021] Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving Safety-aware Motion Prediction with Unseen Vehicles for Autonomous Driving
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.
Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count
The official codes for the ICCV2021 presentation "Uniformity in Heterogeneity: Diving Deep into Count Interval Partition for Crowd Counting"
UEPNet (ICCV2021 Poster Presentation) This repository contains codes for the official implementation in PyTorch of UEPNet as described in Uniformity i
Code repo for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper.
InterpretableMDE A PyTorch implementation for "Towards Interpretable Deep Networks for Monocular Depth Estimation" paper. arXiv link: https://arxiv.or
Code and models for "Rethinking Deep Image Prior for Denoising" (ICCV 2021)
DIP-denosing This is a code repo for Rethinking Deep Image Prior for Denoising (ICCV 2021). Addressing the relationship between Deep image prior and e
Sketch Your Own GAN: Customizing a GAN model with hand-drawn sketches.
Sketch Your Own GAN Project | Paper | Youtube | Slides Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to mat
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition
Zen-NAS: A Zero-Shot NAS for High-Performance Deep Image Recognition How Fast Compare to Other Zero-Shot NAS Proxies on CIFAR-10/100 Pre-trained Model
RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos
RSC-Net: 3D Human Pose, Shape and Texture from Low-Resolution Images and Videos Implementation for "3D Human Pose, Shape and Texture from Low-Resoluti
Neural Scene Flow Prior (NeurIPS 2021 spotlight)
Neural Scene Flow Prior Xueqian Li, Jhony Kaesemodel Pontes, Simon Lucey Will appear on Thirty-fifth Conference on Neural Information Processing Syste
Repository of the paper Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models at ML4AD @ NeurIPS 2021.
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models Code and supplementary materials Repository of the p
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code.
A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code
Chinese Advertisement Board Identification(Pytorch)
Chinese-Advertisement-Board-Identification. We use YoloV5 to extract the ROI of the location of the chinese word. Next, we sort the bounding box and recognize every chinese words which we extracted. The methods which we use are Yolov5, ArgMargin and Focal loss.
Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
Deep-Rep-MFIR Official implementation of Deep Reparametrization of Multi-Frame Super-Resolution and Denoising Publication: Deep Reparametrization of M
MLSpace: Hassle-free machine learning & deep learning development
MLSpace: Hassle-free machine learning & deep learning development
AWS Blog post code for running feature-extraction on images using AWS Batch and Cloud Development Kit (CDK).
Batch processing with AWS Batch and CDK Welcome This repository demostrates provisioning the necessary infrastructure for running a job on AWS Batch u
Road Crack Detection Using Deep Learning Methods
Road-Crack-Detection-Using-Deep-Learning-Methods This is my Diploma Thesis ¨Road Crack Detection Using Deep Learning Methods¨ under the supervision of
Here I will explain the flow to deploy your custom deep learning models on Ultra96V2.
Xilinx_Vitis_AI This repo will help you to Deploy your Deep Learning Model on Ultra96v2 Board. Prerequisites Vitis Core Development Kit 2019.2 This co
cLoops2: full stack analysis tool for chromatin interactions
cLoops2: full stack analysis tool for chromatin interactions Introduction cLoops2 is an extension of our previous work, cLoops. From loop-calling base
Implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork.
YOLOv4-large This is the implementation of "Scaled-YOLOv4: Scaling Cross Stage Partial Network" using PyTorch framwork. YOLOv4-CSP YOLOv4-tiny YOLOv4-
Deep Learning Based Fasion Recommendation System for Ecommerce
Project Name: Fasion Recommendation System for Ecommerce A Deep learning based streamlit web app which can recommened you various types of fasion prod
Readings for "A Unified View of Relational Deep Learning for Polypharmacy Side Effect, Combination Therapy, and Drug-Drug Interaction Prediction."
Polypharmacy - DDI - Synergy Survey The Survey Paper This repository accompanies our survey paper A Unified View of Relational Deep Learning for Polyp
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval - ICCV2021
Self-supervised Product Quantization for Deep Unsupervised Image Retrieval Pytorch implementation of SPQ Accepted to ICCV 2021 - paper Young Kyun Jang
On-device speech-to-index engine powered by deep learning.
On-device speech-to-index engine powered by deep learning.
Traingenerator 🧙 A web app to generate template code for machine learning ✨
Traingenerator 🧙 A web app to generate template code for machine learning ✨ 🎉 Traingenerator is now live! 🎉
AbelNN: Deep Learning Python module from scratch
AbelNN: Deep Learning Python module from scratch I have implemented several neural networks from scratch using only Numpy. I have designed the module
Tool which allow you to detect and translate text.
Text detection and recognition This repository contains tool which allow to detect region with text and translate it one by one. Description Two pretr
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
[SIGMETRICS 2022] One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search
One Proxy Device Is Enough for Hardware-Aware Neural Architecture Search paper | website One Proxy Device Is Enough for Hardware-Aware Neural Architec
Deep-learning X-Ray Micro-CT image enhancement, pore-network modelling and continuum modelling
EDSR modelling A Github repository for deep-learning image enhancement, pore-network and continuum modelling from X-Ray Micro-CT images. The repositor
Deep Learning Algorithms for Hedging with Frictions
Deep Learning Algorithms for Hedging with Frictions This repository contains the Forward-Backward Stochastic Differential Equation (FBSDE) solver and
Codes for CVPR2021 paper "PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization"
PWCLO-Net: Deep LiDAR Odometry in 3D Point Clouds Using Hierarchical Embedding Mask Optimization (CVPR 2021) This is the official implementation of PW
An Open-Source Toolkit for Prompt-Learning.
An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea
Implicit Deep Adaptive Design (iDAD)
Implicit Deep Adaptive Design (iDAD) This code supports the NeurIPS paper 'Implicit Deep Adaptive Design: Policy-Based Experimental Design without Lik
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
causal-bald | Abstract | Installation | Example | Citation | Reproducing Results DUE An implementation of the methods presented in Causal-BALD: Deep B
Official implementation of "Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention" (BMVC 2021).
Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require
deep-prae
Deep Probabilistic Accelerated Evaluation (Deep-PrAE) Our work presents an efficient rare event simulation methodology for black box autonomy using Im
paper: Hyperspectral Remote Sensing Image Classification Using Deep Convolutional Capsule Network
DC-CapsNet This is a tensorflow and keras based implementation of DC-CapsNet for HSI in the Remote Sensing Letters R. Lei et al., "Hyperspectral Remot
A visualisation tool for Deep Reinforcement Learning
DRLVIS - Visualising Deep Reinforcement Learning Created by Marios Sirtmatsis with the support of Alex Bäuerle. DRLVis is an application used for visu
Automatic deep learning for image classification.
AutoDL AutoDL automates machine learning tasks enabling you to easily achieve strong predictive performance in your applications. With just a few line
A python library for highly configurable transformers - easing model architecture search and experimentation.
A python library for highly configurable transformers - easing model architecture search and experimentation.