440 Repositories
Python convolutional-autoencoder Libraries
Saliency - Framework-agnostic implementation for state-of-the-art saliency methods (XRAI, BlurIG, SmoothGrad, and more).
Saliency Methods ๐ด Now framework-agnostic! (Example core notebook) ๐ด ๐ For further explanation of the methods and more examples of the resulting ma
Tensorflow-Project-Template - A best practice for tensorflow project template architecture.
Tensorflow Project Template A simple and well designed structure is essential for any Deep Learning project, so after a lot of practice and contributi
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend
Hyperopt for solving CIFAR-100 with a convolutional neural network (CNN) built with Keras and TensorFlow, GPU backend This project acts as both a tuto
AISTATS 2019: Confidence-based Graph Convolutional Networks for Semi-Supervised Learning
Confidence-based Graph Convolutional Networks for Semi-Supervised Learning Source code for AISTATS 2019 paper: Confidence-based Graph Convolutional Ne
A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling"
SelfGNN A PyTorch implementation of "SelfGNN: Self-supervised Graph Neural Networks without explicit negative sampling" paper, which will appear in Th
An implementation of Deep Graph Infomax (DGI) in PyTorch
DGI Deep Graph Infomax (Veliฤkoviฤ et al., ICLR 2019): https://arxiv.org/abs/1809.10341 Overview Here we provide an implementation of Deep Graph Infom
The code of paper "Block Modeling-Guided Graph Convolutional Neural Networks".
Block Modeling-Guided Graph Convolutional Neural Networks This repository contains the demo code of the paper: Block Modeling-Guided Graph Convolution
Deeper insights into graph convolutional networks for semi-supervised learning
deeper_insights_into_GCNs Deeper insights into graph convolutional networks for semi-supervised learning References data and utils.py come from Implem
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels"
Reference Code for AAAI-20 paper "Multi-Stage Self-Supervised Learning for Graph Convolutional Networks on Graphs with Few Labels" Please refer to htt
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning
Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning Yansong Tang *, Zhenyu Jiang *, Zhenda Xie *, Yue
Curriculum Domain Adaptation for Semantic Segmentation of Urban Scenes, ICCV 2017
AdaptationSeg This is the Python reference implementation of AdaptionSeg proposed in "Curriculum Domain Adaptation for Semantic Segmentation of Urban
PyTorch implementation of Super SloMo by Jiang et al.
Super-SloMo PyTorch implementation of "Super SloMo: High Quality Estimation of Multiple Intermediate Frames for Video Interpolation" by Jiang H., Sun
Machine learning algorithms for many-body quantum systems
NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
Official code for the publication "HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder".
HyFactor Graph-based architectures are becoming increasingly popular as a tool for structure generation. Here, we introduce a novel open-source archit
Source Code for AAAI 2022 paper "Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching"
Graph Convolutional Networks with Dual Message Passing for Subgraph Isomorphism Counting and Matching This repository is an official implementation of
Header-only library for using Keras models in C++.
frugally-deep Use Keras models in C++ with ease Table of contents Introduction Usage Performance Requirements and Installation FAQ Introduction Would
CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network)
CasualHealthcare's Pneumonia detection with Artificial Intelligence (Convolutional Neural Network) This is PneumoniaDiagnose, an artificially intellig
Tensorflow Tutorials using Jupyter Notebook
Tensorflow Tutorials using Jupyter Notebook TensorFlow tutorials written in Python (of course) with Jupyter Notebook. Tried to explain as kindly as po
TensorFlow (Python API) implementation of Neural Style
neural-style-tf This is a TensorFlow implementation of several techniques described in the papers: Image Style Transfer Using Convolutional Neural Net
A deep learning network built with TensorFlow and Keras to classify gender and estimate age.
Convolutional Neural Network (CNN). This repository contains a source code of a deep learning network built with TensorFlow and Keras to classify gend
O-CNN: Octree-based Convolutional Neural Networks for 3D Shape Analysis
O-CNN This repository contains the implementation of our papers related with O-CNN. The code is released under the MIT license. O-CNN: Octree-based Co
[ECCV'20] Convolutional Occupancy Networks
Convolutional Occupancy Networks Paper | Supplementary | Video | Teaser Video | Project Page | Blog Post This repository contains the implementation o
Tensorflow Implementation of ECCV'18 paper: Multimodal Human Motion Synthesis
MT-VAE for Multimodal Human Motion Synthesis This is the code for ECCV 2018 paper MT-VAE: Learning Motion Transformations to Generate Multimodal Human
Pytorch implementation of our paper under review -- 1xN Pattern for Pruning Convolutional Neural Networks
1xN Pattern for Pruning Convolutional Neural Networks (paper) . This is Pytorch re-implementation of "1xN Pattern for Pruning Convolutional Neural Net
Reference code for the paper "Cross-Camera Convolutional Color Constancy" (ICCV 2021)
Cross-Camera Convolutional Color Constancy, ICCV 2021 (Oral) Mahmoud Afifi1,2, Jonathan T. Barron2, Chloe LeGendre2, Yun-Ta Tsai2, and Francois Bleibe
Implementation of Nalbach et al. 2017 paper.
Deep Shading Convolutional Neural Networks for Screen-Space Shading Our project is based on Nalbach et al. 2017 paper. In this project, a set of buffe
Repo for Enhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization
ESACL: Enhanced Seq2Seq Autoencoder via Contrastive Learning for AbstractiveText Summarization This repo is for our paper "Enhanced Seq2Seq Autoencode
An implementation of quantum convolutional neural network with MindQuantum. Huawei, classifying MNIST dataset
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An SE(3)-invariant autoencoder for generating the periodic structure of materials
Crystal Diffusion Variational AutoEncoder This software implementes Crystal Diffusion Variational AutoEncoder (CDVAE), which generates the periodic st
Some code of the implements of Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network
3D-GMPDCNN Geological Modeling Using 3D Pixel-Adaptive and Deformable Convolutional Neural Network PyTorch implementation of "Geological Modeling Usin
Self-Supervised CNN-GCN Autoencoder
GCNDepth Self-Supervised CNN-GCN Autoencoder GCNDepth: Self-supervised monocular depth estimation based on graph convolutional network To be published
PyG (PyTorch Geometric) - A library built upon PyTorch to easily write and train Graph Neural Networks (GNNs)
PyG (PyTorch Geometric) is a library built upon PyTorch to easily write and train Graph Neural Networks (GNNs) for a wide range of applications related to structured data.
PyTorch implementation of normalizing flow models
PyTorch implementation of normalizing flow models
1st Solution For NeurIPS 2021 Competition on ML4CO Dual Task
KIDA: Knowledge Inheritance in Data Aggregation This project releases our 1st place solution on NeurIPS2021 ML4CO Dual Task. Slide and model weights a
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Codes for TIM2021 paper "Anchor-Based Spatio-Temporal Attention 3-D Convolutional Networks for Dynamic 3-D Point Cloud Sequences"
Junction Tree Variational Autoencoder for Molecular Graph Generation (ICML 2018)
Junction Tree Variational Autoencoder for Molecular Graph Generation Official implementation of our Junction Tree Variational Autoencoder https://arxi
SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolutional Networks
SalFBNet This repository includes Pytorch implementation for the following paper: SalFBNet: Learning Pseudo-Saliency Distribution via Feedback Convolu
Bayesian Deep Learning and Deep Reinforcement Learning for Object Shape Error Response and Correction of Manufacturing Systems
Bayesian Deep Learning for Manufacturing 2.0 (dlmfg) Object Shape Error Response (OSER) Digital Lifecycle Management - In Process Quality Improvement
Pytorch code for "Text-Independent Speaker Verification Using 3D Convolutional Neural Networks".
:speaker: Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
Convolutional Neural Network for Text Classification in Tensorflow
This code belongs to the "Implementing a CNN for Text Classification in Tensorflow" blog post. It is slightly simplified implementation of Kim's Convo
Translate darknet to tensorflow. Load trained weights, retrain/fine-tune using tensorflow, export constant graph def to mobile devices
Intro Real-time object detection and classification. Paper: version 1, version 2. Read more about YOLO (in darknet) and download weight files here. In
CNN visualization tool in TensorFlow
tf_cnnvis A blog post describing the library: https://medium.com/@falaktheoptimist/want-to-look-inside-your-cnn-we-have-just-the-right-tool-for-you-ad
Deep Learning & 3D Convolutional Neural Networks for Speaker Verification
TensorFlow implementation of 3D Convolutional Neural Networks for Speaker Verification - Official Project Page - Pytorch Implementation This repositor
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks
Lip Reading - Cross Audio-Visual Recognition using 3D Convolutional Neural Networks - Official Project Page This repository contains the code develope
Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Time Using Noisy Proxies
Deconfounding Temporal Autoencoder (DTA) This is a repository for the paper "Deconfounding Temporal Autoencoder: Estimating Treatment Effects over Tim
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch
Reminder ST-GCN has transferred to MMSkeleton, and keep on developing as an flexible open source toolbox for skeleton-based human understanding. You a
FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection
FCAF3D: Fully Convolutional Anchor-Free 3D Object Detection This repository contains an implementation of FCAF3D, a 3D object detection method introdu
Another pytorch implementation of FCN (Fully Convolutional Networks)
FCN-pytorch-easiest Trying to be the easiest FCN pytorch implementation and just in a get and use fashion Here I use a handbag semantic segmentation f
Inflated i3d network with inception backbone, weights transfered from tensorflow
I3D models transfered from Tensorflow to PyTorch This repo contains several scripts that allow to transfer the weights from the tensorflow implementat
A light weight data augmentation tool for training CNNs and Viola Jones detectors
hey-daug A light weight data augmentation tool for training CNNs and Viola Jones detectors (Haar Cascades). This tool inflates your data by up to six
Convolutional Neural Networks
Darknet Darknet is an open source neural network framework written in C and CUDA. It is fast, easy to install, and supports CPU and GPU computation. D
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network)
BERTAC (BERT-style transformer-based language model with Adversarially pretrained Convolutional neural network) BERTAC is a framework that combines a
[KBS] Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks
#Sentic GCN Introduction This repository was used in our paper: Aspect-Based Sentiment Analysis via Affective Knowledge Enhanced Graph Convolutional N
MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution
Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag
Fully convolutional deep neural network to remove transparent overlays from images
Fully convolutional deep neural network to remove transparent overlays from images
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
PointCNN: Convolution On X-Transformed Points Created by Yangyan Li, Rui Bu, Mingchao Sun, Wei Wu, Xinhan Di, and Baoquan Chen. Introduction PointCNN
PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Study-CSRNet-pytorch This is the PyTorch version repo for CSRNet: Dilated Convolutional Neural Networks for Understanding the Highly Congested Scenes
Pytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
The repository contains the implementations for Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects. Model
Learning Convolutional Neural Networks with Interactive Visualization.
CNN Explainer An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs) For more information,
Official implementation of the paper "Steganographer Detection via a Similarity Accumulation Graph Convolutional Network"
SAGCN - Official PyTorch Implementation | Paper | Project Page This is the official implementation of the paper "Steganographer detection via a simila
Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"
AdderNet: Do We Really Need Multiplications in Deep Learning? This code is a demo of CVPR 2020 paper AdderNet: Do We Really Need Multiplications in De
This is the official repository for our paper: ''Pruning Self-attentions into Convolutional Layers in Single Path''.
Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti
Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19
2s-AGCN Two-Stream Adaptive Graph Convolutional Networks for Skeleton-Based Action Recognition in CVPR19 Note PyTorch version should be 0.3! For PyTor
This is the official repository for our paper: ''Pruning Self-attentions into Convolutional Layers in Single Path''.
Pruning Self-attentions into Convolutional Layers in Single Path This is the official repository for our paper: Pruning Self-attentions into Convoluti
A TensorFlow 2.x implementation of Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners A TensorFlow implementation of Masked Autoencoders Are Scalable Vision Learners [1]. Our implementati
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Delve is a Python package for analyzing the inference dynamics of your PyTorch model.
Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF)
Graph Convolutional Gated Recurrent Neural Network (GCGRNN) Improved from Graph Convolutional Neural Networks with Data-driven Graph Filter (GCNN-DDGF
DivNoising is an unsupervised denoising method to generate diverse denoised samples for any noisy input image. This repository contains the code to reproduce the results reported in the paper https://openreview.net/pdf?id=agHLCOBM5jP
DivNoising: Diversity Denoising with Fully Convolutional Variational Autoencoders Mangal Prakash1, Alexander Krull1,2, Florian Jug2 1Authors contribut
PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identification in Symbolic Scores.
Symbolic Melody Identification This repository is an unofficial PyTorch implementation of the paper:A Convolutional Approach to Melody Line Identifica
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Project looking into use of autoencoder for semi-supervised learning and comparing data requirements compared to supervised learning.
Naszilla is a Python library for neural architecture search (NAS)
A repository to compare many popular NAS algorithms seamlessly across three popular benchmarks (NASBench 101, 201, and 301). You can implement your ow
A simple, fully convolutional model for real-time instance segmentation.
You Only Look At CoefficienTs โโโ โโโ โโโโโโโ โโโ โโโโโโ โโโโโโโโโโโโโโโโ โโโโ โโโโโโโโโโโโโโโโ โโโโโโโโโโโโโโโโโโโโโโโโโ โโโ
A denoising autoencoder + adversarial losses and attention mechanisms for face swapping.
faceswap-GAN Adding Adversarial loss and perceptual loss (VGGface) to deepfakes'(reddit user) auto-encoder architecture. Updates Date Update 2018-08-2
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy
Implementing Graph Convolutional Networks and Information Retrieval Mechanisms using pure Python and NumPy
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks
Self-supervised Point Cloud Prediction Using 3D Spatio-temporal Convolutional Networks This is a Pytorch-Lightning implementation of the paper "Self-s
Deep Convolutional Generative Adversarial Networks
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks Alec Radford, Luke Metz, Soumith Chintala All images in t
ARAE-Tensorflow for Discrete Sequences (Adversarially Regularized Autoencoder)
ARAE Tensorflow Code Code for the paper Adversarially Regularized Autoencoders for Generating Discrete Structures by Zhao, Kim, Zhang, Rush and LeCun
SalGAN: Visual Saliency Prediction with Generative Adversarial Networks
SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr
Train CPPNs as a Generative Model, using Generative Adversarial Networks and Variational Autoencoder techniques to produce high resolution images.
cppn-gan-vae tensorflow Train Compositional Pattern Producing Network as a Generative Model, using Generative Adversarial Networks and Variational Aut
Age Progression/Regression by Conditional Adversarial Autoencoder
Age Progression/Regression by Conditional Adversarial Autoencoder (CAAE) TensorFlow implementation of the algorithm in the paper Age Progression/Regre
Fully Convolutional Refined Auto Encoding Generative Adversarial Networks for 3D Multi Object Scenes
Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes This repository contains the source code for Full
A simple interface for editing natural photos with generative neural networks.
Neural Photo Editor A simple interface for editing natural photos with generative neural networks. This repository contains code for the paper "Neural
FCOS: Fully Convolutional One-Stage Object Detection (ICCV'19)
FCOS: Fully Convolutional One-Stage Object Detection This project hosts the code for implementing the FCOS algorithm for object detection, as presente
๐ Super-scale your images and run experiments with Residual Dense and Adversarial Networks.
Image Super-Resolution (ISR) The goal of this project is to upscale and improve the quality of low resolution images. This project contains Keras impl
Collection of generative models in Tensorflow
tensorflow-generative-model-collections Tensorflow implementation of various GANs and VAEs. Related Repositories Pytorch version Pytorch version of th
This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning].
CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R
Official implementation for "Image Quality Assessment using Contrastive Learning"
Image Quality Assessment using Contrastive Learning Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang, Balu Adsumilli and Alan C. Bovik This is the offi
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
Official implementation of the RAVE model: a Realtime Audio Variational autoEncoder
Pansharpening by convolutional neural networks in the full resolution framework
Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for
Short and long time series classification using convolutional neural networks
time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f
ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels
ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D
Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification tasks
Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta
This repository contains the reference implementation for our proposed Convolutional CRFs.
ConvCRF This repository contains the reference implementation for our proposed Convolutional CRFs in PyTorch (Tensorflow planned). The two main entry-
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation
ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
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