188 Open source projects that are alternatives of or similar to Attack-ImageNet

Code and data for the ICLR 2021 paper "Perceptual Adversarial Robustness: Defense Against Unseen Threat Models".

Training Low-bits DNNs with Stochastic Quantization

Scripts to work with LMDB + PyTorch for Imagenet training

Geometric Adversarial Attacks and Defenses on 3D Point Clouds (3DV 2021)

PyTorch implementation of EfficientNetV2 family

Code and models for the paper Shape-Texture Debiased Neural Network Training (ICLR 2021)

AdvPC: Transferable Adversarial Perturbations on 3D Point Clouds (ECCV 2020)

A collection of SOTA Image Classification Models in PyTorch

Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)

Implementation of the KDD 2020 paper "Graph Structure Learning for Robust Graph Neural Networks"

Self-distillation with Batch Knowledge Ensembling Improves ImageNet Classification

KitanaQA: Adversarial training and data augmentation for neural question-answering models

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

ImageNet model implemented using the Keras Functional API

Unofficial TensorFlow implementation of "AlexNet" architecture.

73.6% GhostNet 1.0x pre-trained model on ImageNet

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

Xception implemented with caffe

Hands on Imagenet training. Unofficial ModelZoo project on Pytorch. MobileNetV3 Top1 75.64🌟 GhostNet1.3x 75.78🌟

Implementation of the WSDM 2021 paper "Node Similarity Preserving Graph Convolutional Networks"

Codes for NeurIPS 2020 paper "Adversarial Weight Perturbation Helps Robust Generalization"

Train faster rcnn on imagine dataset, related blog post: https://andrewliao11.github.io/object/detection/2016/07/23/detection/

TF-NAS: Rethinking Three Search Freedoms of Latency-Constrained Differentiable Neural Architecture Search (ECCV2020)

CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.

Graph Robustness Benchmark: A scalable, unified, modular, and reproducible benchmark for evaluating the adversarial robustness of Graph Machine Learning.

custom implementation alexnet with tensorflow

Natural Language Attacks in a Hard Label Black Box Setting.

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

Attacking Optical Flow (ICCV 2019)

Pytorch code to generate adversarial examples on mnist and ImageNet data.

Bottleneck Transformers for Visual Recognition

Python toolbox to evaluate graph vulnerability and robustness (CIKM 2021)

No description or website provided.

"GAN 인 액션"(한빛미디어, 2020)의 코드 저장소입니다.

[ECCV 2020] Scale Adaptive Network: Learning to Learn Parameterized Classification Networks for Scalable Input Images

Nearly Perfect & Easily Understandable PyTorch Implementation of SKNet

Parametric Contrastive Learning (ICCV2021)

SimpleAICV:pytorch training example on ImageNet(ILSVRC2012)/COCO2017/VOC2007+2012 datasets.Include ResNet/DarkNet/RetinaNet/FCOS/CenterNet/TTFNet/YOLOv3/YOLOv4/YOLOv5/YOLOX.

An Algorithm to Quantify Robustness of Recurrent Neural Networks

Autoencoder trained on ImageNet Using Torch 7

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

Adversarial Attacks on Deep Neural Networks for Time Series Classification

Code for the unrestricted adversarial examples paper (NeurIPS 2018)

A pytorch implementation of "Towards Deep Learning Models Resistant to Adversarial Attacks"

Fast Image Retrieval (FIRe) is an open source project to promote image retrieval research. It implements most of the major binary hashing methods to date, together with different popular backbone networks and public datasets.

Sparse-RS: a versatile framework for query-efficient sparse black-box adversarial attacks

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

[ICCV2021 Oral] Fooling LiDAR by Attacking GPS Trajectory

No description or website provided.

PyTorch implementation of Lambda Network and pretrained Lambda-ResNet

🤖 Cozmo the Robot recognizes objects with TensorFlow

TrojanZoo provides a universal pytorch platform to conduct security researches (especially backdoor attacks/defenses) of image classification in deep learning.

[IEEE Access] "Head Network Distillation: Splitting Distilled Deep Neural Networks for Resource-constrained Edge Computing Systems" and [ACM MobiCom HotEdgeVideo 2019] "Distilled Split Deep Neural Networks for Edge-assisted Real-time Systems"

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

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

ImageNet pre-trained SharpPeleeNet can be used in real-time Semantic Segmentation/Objects Detection

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

This is a collection of algorithms and approaches used in the book adversarial deep learning

Selective Classification For Deep Neural Networks.

Compare neural networks by their feature similarity