Python 3d-convolutional-network Resources

SalGAN: Visual Saliency Prediction with Adversarial Networks Junting Pan Cristian Canton Ferrer Kevin McGuinness Noel O'Connor Jordi Torres Elisa Sayr

Photo-Realistic-Super-Resoluton Torch Implementation of "Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network" [Paper]

Context Encoders: Feature Learning by Inpainting CVPR 2016 [Project Website] [Imagenet Results] Sample results on held-out images: This is the trainin

CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for

pix2pix Project | Arxiv | PyTorch Torch implementation for learning a mapping from input images to output images, for example: Image-to-Image Translat

Image De-raining Using a Conditional Generative Adversarial Network [Paper Link] [Project Page] He Zhang, Vishwanath Sindagi, Vishal M. Patel In this

Fully Convolutional Refined Auto-Encoding Generative Adversarial Networks for 3D Multi Object Scenes This repository contains the source code for Full

Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modeling This repository contains pre-trained models and sampling

Text To Image Synthesis Using Thought Vectors This is an experimental tensorflow implementation of synthesizing images from captions using Skip Though

A Tensorflow implementation of the Text Conditioned Auxiliary Classifier Generative Adversarial Network for Generating Images from text descriptions

Neural Photo Editor A simple interface for editing natural photos with generative neural networks. This repository contains code for the paper "Neural

iGAN: Interactive Image Generation via Generative Adversarial Networks Project | Youtube | Paper Recent projects: [pix2pix]: Torch implementation for

Anime-Face-GAN-Keras A DCGAN to generate anime faces using custom dataset in Keras. Dataset The dataset is created by crawling anime database websites

FCOS: Fully Convolutional One-Stage Object Detection This project hosts the code for implementing the FCOS algorithm for object detection, as presente

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

gans-awesome-applications Curated list of awesome GAN applications and demonstrations. Note: General GAN papers targeting simple image generation such

The GAN Zoo Every week, new GAN papers are coming out and it's hard to keep track of them all, not to mention the incredibly creative ways in which re

Sequence to Sequence (seq2seq) Recurrent Neural Network (RNN) for Time Series Forecasting Note: You can find here the accompanying seq2seq RNN forecas

Keras implementation of a sequence to sequence model for time series prediction using an encoder-decoder architecture. I created this post to share a

CG3 This is the repository for the AAAI 21 paper [Contrastive and Generative Graph Convolutional Networks for Graph-based Semi-Supervised Learning]. R

JBHI-Pytorch This repository contains a reference implementation of the algorithms described in our paper "Self-supervised Multi-modal Hybrid Fusion N

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

Temporal copying and local hallucination for video inpainting This repository contains the implementation of my master's thesis "Temporal copying and

Pytorch implementation of forward and inverse Haar Wavelets 2D

Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data (NeurIPS 2021) This repository will provide the official PyTorch implementa

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi

Z-PNN: Zoom Pansharpening Neural Network Pansharpening by convolutional neural networks in the full resolution framework is a deep learning method for

Nyx-Net: Network Fuzzing with Incremental Snapshots Nyx-Net is fast full-VM snapshot fuzzer for complex network based targets. It's built upon kAFL, R

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

FisherPruning-Pytorch An implementation of Group Fisher Pruning for Practical Network Compression based on pytorch and mmcv Main Functions Pruning f

Task-related Saliency Network For Few-shot learning This is an official implementation in Tensorflow of TRSN. Abstract An essential cue of human wisdo

time-series-classification Short and long time series classification via convolutional neural networks In this project, we present a novel framework f

ROCKET + MINIROCKET ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge D

NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture

Neural Architecture Search Powered by Swarm Intelligence 🐜 DeepSwarm DeepSwarm is an open-source library which uses Ant Colony Optimization to tackle

Uniformer - Pytorch Implementation of Uniformer, a simple attention and 3d convolutional net that achieved SOTA in a number of video classification ta

EZ-Graph EZ Graph is a GUI that allows users to make and train neural networks without writing a single line of code. Requirements python 3 pandas num

PortraitNet Code for the paper "PortraitNet: Real-time portrait segmentation network for mobile device". @ CAD&Graphics 2019 Introduction We propose a

ConvCRF This repository contains the reference implementation for our proposed Convolutional CRFs in PyTorch (Tensorflow planned). The two main entry-

UPSNet: A Unified Panoptic Segmentation Network Introduction UPSNet is initially described in a CVPR 2019 oral paper. Disclaimer This repository is te

PSANet: Point-wise Spatial Attention Network for Scene Parsing (in construction) by Hengshuang Zhao*, Yi Zhang*, Shu Liu, Jianping Shi, Chen Change Lo

Fast-SCNN: Fast Semantic Segmentation Network Unofficial implementation of the model architecture of Fast-SCNN. Real-time Semantic Segmentation and mo

ESPNet: Efficient Spatial Pyramid of Dilated Convolutions for Semantic Segmentation This repository contains the source code of our paper, ESPNet (acc

Dual Attention Network for Scene Segmentation(CVPR2019) Jun Fu, Jing Liu, Haijie Tian, Yong Li, Yongjun Bao, Zhiwei Fang,and Hanqing Lu Introduction W

Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor

Learning to Adapt Structured Output Space for Semantic Segmentation Pytorch implementation of our method for adapting semantic segmentation from the s

Pixel Transposed Convolutional Networks Created by Hongyang Gao, Hao Yuan, Zhengyang Wang and Shuiwang Ji at Texas A&M University. Introduction Pixel

Segmentation-Aware Convolutional Networks Using Local Attention Masks [Project Page] [Paper] Segmentation-aware convolution filters are invariant to b

Tensorflow implementation of Learning Deconvolution Network for Semantic Segmentation. Install Instructions Works with tensorflow 1.11.0 and uses the

DeconvNet: Learning Deconvolution Network for Semantic Segmentation Created by Hyeonwoo Noh, Seunghoon Hong and Bohyung Han at POSTECH Acknowledgement

PSPNet_tensorflow Important Code is fine for inference. However, the training code is just for reference and might be only used for fine-tuning. If yo

PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+

Pyramid Scene Parsing Network by Hengshuang Zhao, Jianping Shi, Xiaojuan Qi, Xiaogang Wang, Jiaya Jia, details are in project page. Introduction This

Keras-ICNet [paper] Keras implementation of Real-Time Semantic Segmentation on High-Resolution Images. Training in progress! Requisites Python 3.6.3 K

The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation: Work In Progress, Results can't be replicated yet with the m

FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th

Introduction This repo contains the code to train and evaluate FC-DenseNets as described in The One Hundred Layers Tiramisu: Fully Convolutional Dense

LinkNet This repository contains our Torch7 implementation of the network developed by us at e-Lab. You can go to our blogpost or read the article Lin

ENet This work has been published in arXiv: ENet: A Deep Neural Network Architecture for Real-Time Semantic Segmentation. Packages: train contains too

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

keras-fcn A re-implementation of Fully Convolutional Networks with Keras Installation Dependencies keras tensorflow Install with pip $ pip install git

Keras-FCN This repository contains my implementation of Fully Convolutional Networks in Keras (Tensorflow backend). Currently, semantic segmentation c

Using fully convolutional networks for semantic segmentation (Shelhamer et al.) with caffe for the cityscapes dataset How to get started Download the

FCN-semantic-segmentation Simple end-to-end semantic segmentation using fully convolutional networks [1]. Takes a pretrained 34-layer ResNet [2], remo

fcn - Fully Convolutional Networks Chainer implementation of Fully Convolutional Networks. Installation pip install fcn Inference Inference is done as

##A tensorflow implementation of Fully Convolutional Networks For Semantic Segmentation. #USAGE To run the trained classifier on some images: python w

FCN.tensorflow Tensorflow implementation of Fully Convolutional Networks for Semantic Segmentation (FCNs). The implementation is largely based on the

FCN_via_Keras FCN FCN (Fully Convolutional Network) is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This

Keras-FCN Fully convolutional networks and semantic segmentation with Keras. Models Models are found in models.py, and include ResNet and DenseNet bas

Update An example on how to integrate this code into your own semantic segmentation pipeline can be found in my KittiSeg project repository. tensorflo

Fully Convolutional Networks for Semantic Segmentation This is the reference implementation of the models and code for the fully convolutional network

MatConvNet implementation of the FCN models for semantic segmentation This package contains an implementation of the FCN models (training and evaluati

Torch implementation of SegNet and deconvolutional network

SegNet SegNet is a TensorFlow implementation of the segmentation network proposed by Kendall et al., with cool features like strided deconvolution, a

Segnet is deep fully convolutional neural network architecture for semantic pixel-wise segmentation. This is implementation of http://arxiv.org/pdf/15

Caffe SegNet This is a modified version of Caffe which supports the SegNet architecture As described in SegNet: A Deep Convolutional Encoder-Decoder A

Retina blood vessel segmentation with a convolution neural network (U-net) This repository contains the implementation of a convolutional neural netwo

Tensorflow Unet Warning This project is discontinued in favour of a Tensorflow 2 compatible reimplementation of this project found under https://githu

Deep Learning Tutorial for Kaggle Ultrasound Nerve Segmentation competition, using Keras This tutorial shows how to use Keras library to build deep ne

ZF_UNET_224 Pretrained Model Modification of convolutional neural net "UNET" for image segmentation in Keras framework Requirements Python 3.*, Keras

AlbUNet-1D-2D-Tensorflow-Keras This repository contains 1D and 2D Signal Segmentation Model Builder for AlbUNet and several of its variants developed

Transformers: from NLP to CV This is a practical introduction to Transformers from Natural Language Processing (NLP) to Computer Vision (CV) Introduct

TTSR Official PyTorch implementation of the paper Learning Texture Transformer Network for Image Super-Resolution accepted in CVPR 2020. Contents Intr

Quiver Interactive convnet features visualization for Keras The quiver workflow Video Demo Build your model in keras model = Model(...) Launch the vis

Neural network-based build time estimation for additive manufacturing Oh, Y., Sharp, M., Sprock, T., & Kwon, S. (2021). Neural network-based build tim

On the Equivalence between Neural Network and Support Vector Machine Codes for NeurIPS 2021 paper "On the Equivalence between Neural Network and Suppo

Climate Modeling with Neural Diffusion Equation Introduction This is the repository of our accepted ICDM 2021 paper "Climate Modeling with Neural Diff

HINet Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet. Dependencies NumPy PyTorch, preferabl

Invertible Image Denoising This is the PyTorch implementation of paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR 20

Attention-Guided-Contextual-Feature-Fusion-Network-for-Salient-Object-Detection This repo. is an implementation of ACFFNet, which is accepted for in I

Real-time stock predictions with deep learning and news scraping This repository contains a partial implementation of my bachelor's thesis "Real-time

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ICS-Visualizer is an interactive Industrial Control Systems (ICS) network graph that contains up-to-date ICS metadata (Name, company, port, user manua

FPS-Net Code for "FPS-Net: A convolutional fusion network for large-scale LiDAR point cloud segmentation", accepted by ISPRS journal of Photogrammetry

Yolo-Powered-Detector A object detecting neural network powered by the yolo architecture and leveraging the PyTorch framework and associated libraries

Inhomogeneous Social Recommendation with Hypergraph Convolutional Networks This is our Pytorch implementation for the paper: Zirui Zhu, Chen Gao, Xu C

EquivariantSelfAttention An implementation of Equivariant e2 convolutional kernals into a convolutional self attention network, applied to radio astro

TradingBot6M Kennedy Institute of Rheumatology University of Oxford Project November 2019 Run Change api.txt to binance api key: https://www.binance.c