231 Open source projects that are alternatives of or similar to Dcgan

Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"

Deep Learning Super Sampling with Deep Convolutional Generative Adversarial Networks.

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

Torch implementation of various types of GAN (e.g. DCGAN, ALI, Context-encoder, DiscoGAN, CycleGAN, EBGAN, LSGAN)

PyTorch implementation of image classification models for CIFAR-10/CIFAR-100/MNIST/FashionMNIST/Kuzushiji-MNIST/ImageNet

Python scripts for performing object detection with the 1000 labels of the ImageNet dataset in ONNX. The repository combines a class agnostic object localizer to first detect the objects in the image, and next a ResNet50 model trained on ImageNet is used to label each box.

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

PyTorch to Keras model convertor

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Interactive Image Generation via Generative Adversarial Networks

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Open Set Recognition

DCGAN LSGAN WGAN-GP DRAGAN Tensorflow 2

TensorFlow ImageNet - Training and SOTA checkpoints

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🔬 Some personal research code on analyzing CNNs. Started with a thorough exploration of Stanford's Tiny-Imagenet-200 dataset.

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

深度卷积生成对抗网络（DCGAN）—— 动漫妹子头像生成 2018-10-22

[CVPR 2016] Unsupervised Feature Learning by Image Inpainting using GANs

Chainer implementation of Least Squares GAN (LSGAN)

Python package with source code from the course "Creative Applications of Deep Learning w/ TensorFlow"

PyTorch implementation of Lambda Network and pretrained Lambda-ResNet

Awesome Generative Adversarial Networks with tensorflow

Selective Classification For Deep Neural Networks.

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Unofficial TensorFlow implementation of "AlexNet" architecture.

Classification models trained on ImageNet. Keras.

A collection of SOTA Image Classification Models in PyTorch

🔥 Reproducibly benchmarking Keras and PyTorch models

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

MEAL V2: Boosting Vanilla ResNet-50 to 80%+ Top-1 Accuracy on ImageNet without Tricks

Etiketai is an online tool designed to label images, useful for training AI models

Official Pytorch implementation of ReXNet (Rank eXpansion Network) with pretrained models

Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

Books, Presentations, Workshops, Notebook Labs, and Model Zoo for Software Engineers and Data Scientists wanting to learn the TF.Keras Machine Learning framework

Translate text to image in Keras using GAN and Word2Vec as well as recurrent neural networks

Unofficial PyTorch Reimplementation of RandAugment.

Dataset Management Framework, a Python library and a CLI tool to build, analyze and manage Computer Vision datasets.

OpenMMLab Image Classification Toolbox and Benchmark

Training Low-bits DNNs with Stochastic Quantization

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

Tool to evaluate deep-learning detection and segmentation models, and to create datasets

Deep Learning and Reinforcement Learning Library for Scientists and Engineers 🔥

Repository for implementation of generative models with Tensorflow 1.x

PyTorch implementation of PNASNet-5 on ImageNet

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

Friendly machine learning for the web! 🤖

PyTorch implementation of EfficientNetV2 family

Comparison of famous convolutional neural network models

Bottleneck Transformers for Visual Recognition

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The Simplest DCGAN Implementation

A tensorflow implementation of "Deep Convolutional Generative Adversarial Networks"

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

PyTorch to Keras model convertor

Corruption and Perturbation Robustness (ICLR 2019)

Pytorch Implementation of: "Exploring Randomly Wired Neural Networks for Image Recognition"