1263 Open source projects that are alternatives of or similar to Ghostnet

Implementation of EfficientNet model. Keras and TensorFlow Keras.

Classification models trained on ImageNet. Keras.

A collection of SOTA Image Classification Models in PyTorch

73.6% GhostNet 1.0x pre-trained model on ImageNet

Mobilenet V2(Inverted Residual) Implementation & Trained Weights Using Tensorflow

Official PyTorch Implementation of Long-Short Transformer (NeurIPS 2021).

You Only Look at One Sequence (NeurIPS 2021)

[ICCV 2019] Harmonious Bottleneck on Two Orthogonal Dimensions

PyTorch-style and human-readable RegNet with a spectrum of pre-trained models

74.3% MobileNetV3-Large and 67.2% MobileNetV3-Small model on ImageNet

Tutorial for computer vision and machine learning in PHP 7/8 by opencv (installation + examples + documentation)

[CVPR2020] f-BRS: Rethinking Backpropagating Refinement for Interactive Segmentation https://arxiv.org/abs/2001.10331

The Tensorflow, Keras implementation of Swin-Transformer and Swin-UNET

LiBai(李白): A Toolbox for Large-Scale Distributed Parallel Training

TransMorph: Transformer for Unsupervised Medical Image Registration (PyTorch)

Easily train or fine-tune SOTA computer vision models with one open source training library

PiGallery: AI-powered Self-hosted Secure Multi-user Image Gallery and Detailed Image analysis using Machine Learning, EXIF Parsing and Geo Tagging

Deep Learning Transformer models in MATLAB

Unofficial PyTorch Reimplementation of RandAugment.

Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.

Programming Assignments and Lectures for Stanford's CS 231: Convolutional Neural Networks for Visual Recognition

Making decision trees competitive with neural networks on CIFAR10, CIFAR100, TinyImagenet200, Imagenet

[CVPR2020] GhostNet: More Features from Cheap Operations

Convolutional Neural Networks to predict the aesthetic and technical quality of images.

Corruption and Perturbation Robustness (ICLR 2019)

Fine-tune pretrained Convolutional Neural Networks with PyTorch

Evaluation of the CNN design choices performance on ImageNet-2012.

A Robustly Optimized BERT Pretraining Approach for Vietnamese

Nested Hierarchical Transformer https://arxiv.org/pdf/2105.12723.pdf

Pytorch implementation of "All Tokens Matter: Token Labeling for Training Better Vision Transformers"

[MICCAI2022] This is an official PyTorch implementation for A Robust Volumetric Transformer for Accurate 3D Tumor Segmentation

Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet

SOTA Semantic Segmentation Models in PyTorch

(CVPR 2021, Oral) Dynamic Slimmable Network

pix2tex: Using a ViT to convert images of equations into LaTeX code.

a collection of visualization function

SwinIR: Image Restoration Using Swin Transformer (official repository)

(ECCV 2020) Tensorflow implementation of A Generic Visualization Approach for Convolutional Neural Networks

Tensorflow implementation of "Compounding the Performance Improvements of Assembled Techniques in a Convolutional Neural Network"

Segmentation models with pretrained backbones. PyTorch.

ImageNet pre-trained models with batch normalization for the Caffe framework

Pyramidal Convolution: Rethinking Convolutional Neural Networks for Visual Recognition (https://arxiv.org/pdf/2006.11538.pdf)

Deep Pose Estimation implemented using Tensorflow with Custom Architectures for fast inference.

BERT for Multitask Learning

Class-Balanced Loss Based on Effective Number of Samples. CVPR 2019

Implementation of State-of-the-art Text Classification Models in Pytorch

MobileNetV3 in pytorch and ImageNet pretrained models

OpenMMLab Image Classification Toolbox and Benchmark

A PyTorch implementation of EfficientNet and EfficientNetV2 (coming soon!)

A light-weight, power efficient, and general purpose convolutional neural network

Official repository for the "Big Transfer (BiT): General Visual Representation Learning" paper.

Detecting Pneumonia in Chest X-ray Images using Convolutional Neural Network and Pretrained Models

Keras implementation of BERT with pre-trained weights

Model Compression Based on Geoffery Hinton's Logit Regression Method in Keras applied to MNIST 16x compression over 0.95 percent accuracy.An Implementation of "Distilling the Knowledge in a Neural Network - Geoffery Hinton et. al"

Code for Switchable Normalization from "Differentiable Learning-to-Normalize via Switchable Normalization", https://arxiv.org/abs/1806.10779

Improved Residual Networks (https://arxiv.org/pdf/2004.04989.pdf)

Official PyTorch Implementation for "Rotate to Attend: Convolutional Triplet Attention Module." [WACV 2021]

72.8% MobileNetV2 1.0 model on ImageNet and a spectrum of pre-trained MobileNetV2 models

Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

PSPNet in Chainer