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COCO and D2-City
The dataset used in the paper is COCO and D2-City, which are commonly used detection datasets. -
Face Recognition
Face recognition is a popular form of biometric authentication and due to its widespread use, attacks have become more common as well. Recent studies show that Face Recognition... -
Imperceptible, Robust, and Targeted Adversarial Examples for Automatic Speech...
This paper presents a well-known music identification method and implements it as a neural net. -
Google Cloud Vision
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the Google Cloud Vision platform to test their attack. -
Celeb-DF dataset
The dataset used for testing the effectiveness of Landmark Breaker in disrupting facial landmark extraction and obstructing DeepFake generation. -
Imagenette
The Imagenette dataset used in the paper for class density and dataset quality in high-dimensional, unstructured data. -
Breast Cancer Dataset
Breast cancer dataset where mammograms have been labeled independently by three doctors. Ground-truth has been obtained through a biopsy, not available to the algorithm nor the... -
MNIST and CIFAR-10
The MNIST dataset is a large dataset of handwritten digits, and the CIFAR-10 dataset is a dataset of images from 10 different classes. -
Alibaba Tianchi competition: Alibaba-Tsinghua Adversarial Challenge on Object...
The dataset used in the paper is the Alibaba Tianchi competition: Alibaba-Tsinghua Adversarial Challenge on Object Detection. -
Certified Human Trajectory Prediction
Trajectory prediction plays an essential role in autonomous vehicles. While numerous strategies have been developed to enhance the robustness of trajectory prediction models,... -
SAGA: Spectral Adversarial Geometric Attack on 3D Meshes
A novel framework for a geometric adversarial attack on 3D mesh autoencoders. -
NeurIPS'17 adversarial competition dataset
The dataset used in the paper is not explicitly described, but it is mentioned that the authors used the NeurIPS'17 adversarial competition dataset, compatible with ImageNet,... -
Robustness of SAM: Segment Anything under corruptions and beyond
This work investigates the robustness of SAM to corruptions and adversarial attacks. -
Adversarial Attacks on Video Object Segmentation with Hard Region Discovery
Video object segmentation has been applied to various computer vision tasks, such as video editing, autonomous driving, and human-robot interaction. -
CIFAR-10 and NIPS-W
The dataset used in the paper is CIFAR-10 and NIPS-W, which are benchmark datasets for image classification and adversarial attacks. -
From Sound Representation to Model Robustness
This paper investigates the impact of different standard environmental sound representations (spectrograms) on the recognition performance and adversarial attack robustness of a... -
CycleAdvGAN: integration of adversarial attack and defense
The MNIST and CIFAR10 datasets are used to evaluate the Cycle-Consistent Adversarial GAN (CycleAdvGAN) for image classification.
