95 Repositories
Python resize-convolution Libraries
ConvMAE: Masked Convolution Meets Masked Autoencoders
ConvMAE ConvMAE: Masked Convolution Meets Masked Autoencoders Peng Gao1, Teli Ma1, Hongsheng Li2, Jifeng Dai3, Yu Qiao1, 1 Shanghai AI Laboratory, 2 M
Classification models 1D Zoo - Keras and TF.Keras
Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet
Python script that takes an Impulse response .wav and a input .wav to demonstrate audio convolution.
convolver Python script that takes an Impulse response .wav and a input .wav to demonstrate audio convolution. Created by Sean Higley [email protected]
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.
PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my
Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentation"
Hyper-Convolution Networks for Biomedical Image Segmentation Code for our WACV 2022 paper "Hyper-Convolution Networks for Biomedical Image Segmentatio
Brain tumor detection using Convolution-Neural Network (CNN)
Detect and Classify Brain Tumor using CNN. A system performing detection and classification by using Deep Learning Algorithms using Convolution-Neural Network (CNN).
GTK and Python based, simple multiple image editor tool
System Monitoring Center GTK3 and Python3 based, simple multiple image editor tool. Note: Development of this application is not completed yet. The ap
Automatic Number Plate Recognition using Contours and Convolution Neural Networks (CNN)
Cite our paper if you find this project useful https://www.ijariit.com/manuscripts/v7i4/V7I4-1139.pdf Abstract Image processing technology is used in
TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffic Environments for IV 2022.
TorchGRL TorchGRL is the source code for our paper Graph Convolution-Based Deep Reinforcement Learning for Multi-Agent Decision-Making in Mixed Traffi
Official PyTorch Implementation of paper EAN: Event Adaptive Network for Efficient Action Recognition
Official PyTorch Implementation of paper EAN: Event Adaptive Network for Efficient Action Recognition
A simple code to convert image format and channel as well as resizing and renaming multiple images.
Rename-Resize-and-convert-multiple-images A simple code to convert image format and channel as well as resizing and renaming multiple images. This cod
PyQt Custom Frameless Main Window (Enable to move and resize)
pyqt-custom-frameless-mainwindow PyQt Custom Frameless Main Window (Enable to move and resize) Requirements PyQt5 = 5.8 Setup pip3 install git+https:
Helper to organize your windows on your desktop.
The script of positionsing windows on the screen. How does it work? Select your window to move/res
POCO: Point Convolution for Surface Reconstruction
POCO: Point Convolution for Surface Reconstruction by: Alexandre Boulch and Renaud Marlet Abstract Implicit neural networks have been successfully use
The VarCNN is an Convolution Neural Network based approach to automate Video Assistant Referee in football.
VarCnn: The Deep Learning Powered VAR
MoCoPnet - Deformable 3D Convolution for Video Super-Resolution
Deformable 3D Convolution for Video Super-Resolution Pytorch implementation of l
Tool made for the FWA Yearbook Team to resize multiple images quickly.
ImageResize Tool Tool made for the FWA Yearbook Team to resize multiple images quickly. Make sure to check this repo for future updates How to Use The
NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions
NeoDTI NeoDTI: Neural integration of neighbor information from a heterogeneous network for discovering new drug-target interactions (Bioinformatics).
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition"
Tensorflow Implementation for "Pre-trained Deep Convolution Neural Network Model With Attention for Speech Emotion Recognition" Pre-trained Deep Convo
Dynamics-aware Adversarial Attack of 3D Sparse Convolution Network
Leaded Gradient Method (LGM) This repository contains the PyTorch implementation for paper Dynamics-aware Adversarial Attack of 3D Sparse Convolution
ConvBERT: Improving BERT with Span-based Dynamic Convolution
ConvBERT Introduction In this repo, we introduce a new architecture ConvBERT for pre-training based language model. The code is tested on a V100 GPU.
Implementation of Research Paper "Learning to Enhance Low-Light Image via Zero-Reference Deep Curve Estimation"
Zero-DCE and Zero-DCE++(Lite architechture for Mobile and edge Devices) Papers Abstract The paper presents a novel method, Zero-Reference Deep Curve E
The official implementation of "Rethink Dilated Convolution for Real-time Semantic Segmentation"
RegSeg The official implementation of "Rethink Dilated Convolution for Real-time Semantic Segmentation" Paper: arxiv D block Decoder Setup Install the
Dilated Convolution with Learnable Spacings PyTorch
Dilated-Convolution-with-Learnable-Spacings-PyTorch Ismail Khalfaoui Hassani Dilated Convolution with Learnable Spacings (abbreviated to DCLS) is a no
This is implementation of AlexNet(2012) with 3D Convolution on TensorFlow (AlexNet 3D).
AlexNet_3dConv TensorFlow implementation of AlexNet(2012) by Alex Krizhevsky, with 3D convolutiional layers. 3D AlexNet Network with a standart AlexNe
Re-implement CycleGAN in Tensorlayer
CycleGAN_Tensorlayer Re-implement CycleGAN in TensorLayer Original CycleGAN Improved CycleGAN with resize-convolution Prerequisites: TensorLayer Tenso
DeepFill v1/v2 with Contextual Attention and Gated Convolution, CVPR 2018, and ICCV 2019 Oral
Generative Image Inpainting An open source framework for generative image inpainting task, with the support of Contextual Attention (CVPR 2018) and Ga
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
Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting
QAConv Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting This PyTorch code is proposed in
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
Spatial Sparse Convolution Library
SpConv: Spatially Sparse Convolution Library PyPI Install Downloads CPU (Linux Only) pip install spconv CUDA 10.2 pip install spconv-cu102 CUDA 11.1 p
A PyTorch implementation of "CoAtNet: Marrying Convolution and Attention for All Data Sizes".
CoAtNet Overview This is a PyTorch implementation of CoAtNet specified in "CoAtNet: Marrying Convolution and Attention for All Data Sizes", arXiv 2021
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
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation.
FastFCN: Rethinking Dilated Convolution in the Backbone for Semantic Segmentation [Project] [Paper] [arXiv] [Home] Official implementation of FastFCN:
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
Dilated Convolution for Semantic Image Segmentation
Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper
Fully Convolutional DenseNet (A.K.A 100 layer tiramisu) for semantic segmentation of images implemented in TensorFlow.
FC-DenseNet-Tensorflow This is a re-implementation of the 100 layer tiramisu, technically a fully convolutional DenseNet, in TensorFlow (Tiramisu). Th
Unofficial PyTorch implementation of the Adaptive Convolution architecture for image style transfer
AdaConv Unofficial PyTorch implementation of the Adaptive Convolution architecture for image style transfer from "Adaptive Convolutions for Structure-
Script to rename and resize folders of images
script to rename and resize folders of images
psgresizer - a PySimpleGUI application that will resize your images and BASE64 encode them.
psgresizer A PySimpleGUI Application Resize your images quickly and easily with this GUI application. Resizes and encodes to Base64 so that the result
BMVC 2021 Oral: code for BI-GCN: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation
BMVC 2021 BI-GConv: Boundary-Aware Input-Dependent Graph Convolution for Biomedical Image Segmentation Necassary Dependencies: PyTorch 1.2.0 Python 3.
Implementation of ConvMixer-Patches Are All You Need? in TensorFlow and Keras
Patches Are All You Need? - ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in t
an implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
Key information extraction from invoice document with Graph Convolution Network
Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro
Understanding Convolutional Neural Networks from Theoretical Perspective via Volterra Convolution
nnvolterra Run Code Compile first: make compile Run all codes: make all Test xconv: make npxconv_test MNIST dataset needs to be downloaded, converted
Implementation of ConvMixer in TensorFlow and Keras
ConvMixer ConvMixer, an extremely simple model that is similar in spirit to the ViT and the even-more-basic MLP-Mixer in that it operates directly on
Optimize/Compress images using python
Image Optimization Using Python steps to run the script run the command to install the required libraries pip install -r requirements.txt create a dir
An implementation of Video Frame Interpolation via Adaptive Separable Convolution using PyTorch
This work has now been superseded by: https://github.com/sniklaus/revisiting-sepconv sepconv-slomo This is a reference implementation of Video Frame I
This is an official pytorch implementation of Fast Fourier Convolution.
Fast Fourier Convolution (FFC) for Image Classification This is the official code of Fast Fourier Convolution for image classification on ImageNet. Ma
Continuous Conditional Random Field Convolution for Point Cloud Segmentation
CRFConv This repository is the implementation of "Continuous Conditional Random Field Convolution for Point Cloud Segmentation" 1. Setup 1) Building c
Fast batch image resizer and rotator for JPEG and PNG images.
imgp is a command line image resizer and rotator for JPEG and PNG images.
CropImage is a simple toolkit for image cropping, detecting and cropping main body from pictures.
CropImage is a simple toolkit for image cropping, detecting and cropping main body from pictures. Support face and saliency detection.
The GitHub repository for the paper: “Time Series is a Special Sequence: Forecasting with Sample Convolution and Interaction“.
SCINet This is the original PyTorch implementation of the following work: Time Series is a Special Sequence: Forecasting with Sample Convolution and I
PyTorch implementation of Deformable Convolution
PyTorch implementation of Deformable Convolution !!!Warning: There is some issues in this implementation and this repo is not maintained any more, ple
[ICCV2021] Official code for "Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition"
CTR-GCN This repo is the official implementation for Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition. The pap
Adaptive Graph Convolution for Point Cloud Analysis
Adaptive Graph Convolution for Point Cloud Analysis This repository contains the implementation of AdaptConv for point cloud analysis. Adaptive Graph
Demonstrates how to divide a DL model into multiple IR model files (division) and introduce a simplest way to implement a custom layer works with OpenVINO IR models.
Demonstration of OpenVINO techniques - Model-division and a simplest-way to support custom layers Description: Model Optimizer in Intel(r) OpenVINO(tm
Classifying audio using Wavelet transform and deep learning
Audio Classification using Wavelet Transform and Deep Learning A step-by-step tutorial to classify audio signals using continuous wavelet transform (C
Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine.
img2dataset Easily turn large sets of image urls to an image dataset. Can download, resize and package 100M urls in 20h on one machine. Also supports
Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices, ACM Multimedia 2021
Codes for ECBSR Edge-oriented Convolution Block for Real-time Super Resolution on Mobile Devices Xindong Zhang, Hui Zeng, Lei Zhang ACM Multimedia 202
PyTorch implementation of Deformable Convolution
Deformable Convolutional Networks in PyTorch This repo is an implementation of Deformable Convolution. Ported from author's MXNet implementation. Buil
This is the codebase for the ICLR 2021 paper Trajectory Prediction using Equivariant Continuous Convolution
Trajectory Prediction using Equivariant Continuous Convolution (ECCO) This is the codebase for the ICLR 2021 paper Trajectory Prediction using Equivar
PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal Convolutions for Action Recognition"
R2Plus1D-PyTorch PyTorch implementation of the R2Plus1D convolution based ResNet architecture described in the paper "A Closer Look at Spatiotemporal
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
🍀 Pytorch implementation of various Attention Mechanisms, MLP, Re-parameter, Convolution, which is helpful to further understand papers.⭐⭐⭐
Implements an infinite sum of poisson-weighted convolutions
An infinite sum of Poisson-weighted convolutions Kyle Cranmer, Aug 2018 If viewing on GitHub, this looks better with nbviewer: click here Consider a v
A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)
Graph Wavelet Neural Network ⠀⠀ A PyTorch implementation of Graph Wavelet Neural Network (ICLR 2019). Abstract We present graph wavelet neural network
A PyTorch implementation of "Signed Graph Convolutional Network" (ICDM 2018).
SGCN ⠀ A PyTorch implementation of Signed Graph Convolutional Network (ICDM 2018). Abstract Due to the fact much of today's data can be represented as
A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).
GAM ⠀⠀ A PyTorch implementation of Graph Classification Using Structural Attention (KDD 2018). Abstract Graph classification is a problem with practic
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).
SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s
An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).
MixHop and N-GCN ⠀ A PyTorch implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019)
A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).
CapsGNN ⠀⠀ A PyTorch implementation of Capsule Graph Neural Network (ICLR 2019). Abstract The high-quality node embeddings learned from the Graph Neur
A PyTorch implementation of "Semi-Supervised Graph Classification: A Hierarchical Graph Perspective" (WWW 2019)
SEAL ⠀⠀⠀ A PyTorch implementation of Semi-Supervised Graph Classification: A Hierarchical Graph Perspective (WWW 2019) Abstract Node classification an
A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).
ClusterGCN ⠀⠀ A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019). A
Classify bird species based on their songs using SIamese Networks and 1D dilated convolutions.
The goal is to classify different birds species based on their songs/calls. Spectrograms have been extracted from the audio samples and used as features for classification.
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution
CondLaneNet: a Top-to-down Lane Detection Framework Based on Conditional Convolution This is the official implementation code of the paper "CondLaneNe
Code for the RA-L (ICRA) 2021 paper "SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition"
SeqNet: Learning Descriptors for Sequence-Based Hierarchical Place Recognition [ArXiv+Supplementary] [IEEE Xplore RA-L 2021] [ICRA 2021 YouTube Video]
Implementation for Simple Spectral Graph Convolution in ICLR 2021
Simple Spectral Graph Convolutional Overview This repo contains an example implementation of the Simple Spectral Graph Convolutional (S^2GC) model. Th
We will release the code of "ConTNet: Why not use convolution and transformer at the same time?" in this repo
ConTNet Introduction ConTNet (Convlution-Tranformer Network) is proposed mainly in response to the following two issues: (1) ConvNets lack a large rec
Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"
ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip
Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"
ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip
official code for dynamic convolution decomposition
Revisiting Dynamic Convolution via Matrix Decomposition (ICLR 2021) A pytorch implementation of DCD. If you use this code in your research please cons
PyTorch reimplementation of the paper Involution: Inverting the Inherence of Convolution for Visual Recognition [CVPR 2021].
Involution: Inverting the Inherence of Convolution for Visual Recognition Unofficial PyTorch reimplementation of the paper Involution: Inverting the I
Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution
FAU Implementation of the paper: Facial Action Unit Intensity Estimation via Semantic Correspondence Learning with Dynamic Graph Convolution. Yingruo
Implementation of the "PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences" paper.
PSTNet: Point Spatio-Temporal Convolution on Point Cloud Sequences Introduction Point cloud sequences are irregular and unordered in the spatial dimen
(CVPR 2021) PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds
PAConv: Position Adaptive Convolution with Dynamic Kernel Assembling on Point Clouds by Mutian Xu*, Runyu Ding*, Hengshuang Zhao, and Xiaojuan Qi. Int
PyTorch Implementation of CvT: Introducing Convolutions to Vision Transformers
CvT: Introducing Convolutions to Vision Transformers Pytorch implementation of CvT: Introducing Convolutions to Vision Transformers Usage: img = torch
Diverse Branch Block: Building a Convolution as an Inception-like Unit
Diverse Branch Block: Building a Convolution as an Inception-like Unit (PyTorch) (CVPR-2021) DBB is a powerful ConvNet building block to replace regul
Code for Mesh Convolution Using a Learned Kernel Basis
Mesh Convolution This repository contains the implementation (in PyTorch) of the paper FULLY CONVOLUTIONAL MESH AUTOENCODER USING EFFICIENT SPATIALLY
This is the implementation of the paper "Gated Recurrent Convolution Neural Network for OCR"
Gated Recurrent Convolution Neural Network for OCR This project is an implementation of the GRCNN for OCR. For details, please refer to the paper: htt
[CVPR 2021] Involution: Inverting the Inherence of Convolution for Visual Recognition, a brand new neural operator
involution Official implementation of a neural operator as described in Involution: Inverting the Inherence of Convolution for Visual Recognition (CVP
Official pytorch implementation of paper "Inception Convolution with Efficient Dilation Search" (CVPR 2021 Oral).
IC-Conv This repository is an official implementation of the paper Inception Convolution with Efficient Dilation Search. Getting Started Download Imag
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
MINIROCKET: A Very Fast (Almost) Deterministic Transform for Time Series Classification
PyTorch implementation of "Conformer: Convolution-augmented Transformer for Speech Recognition" (INTERSPEECH 2020)
PyTorch implementation of Conformer: Convolution-augmented Transformer for Speech Recognition. Transformer models are good at capturing content-based
A Temporal Extension Library for PyTorch Geometric
Documentation | External Resources | Datasets PyTorch Geometric Temporal is a temporal (dynamic) extension library for PyTorch Geometric. The library