135 datasets found

The UBnormal dataset is a recent and large dataset proposed for supervised anomaly detection. In contrast to other benchmarks, it is a synthetic dataset created with Cinema4D....

The Avenue data set consists of 16 training videos with a total 15328 frames and 21 test videos with a total of 15324.

The dataset used in this work is a custom synthetic dataset generated using the liquid-dsp library, containing 600000 examples of each of 13.8 million examples, with SNRs...

The BUSI dataset is a collection of ultrasound images depicting normal, benign, and malignant breast cancer cases along with their corresponding segmentation maps.

The CMS trigger rate monitoring dataset is used for anomaly detection tasks.

Metro do Porto dataset for predictive maintenance, a real-world case study on anomaly detection and explanation for fault prediction.

The dataset is a benchmark for self-supervised learning on long-tailed data. It contains 115.8K images with 1000 categories, ranging from 1,280 to 5 in terms of class cardinality.

The ODDS dataset is a collection of real-world datasets for anomaly detection, including Cardiotocography, Thyroid, and Musk.

The dataset used in this paper is the WSN dataset of the Intel Berkeley Research Lab (IBRL).

The ShanghaiTech dataset includes 330 training and 107 test videos recorded at 13 different background locations.

The CUHK Avenue dataset comprises one scene captured by a camera looking at an avenue near a subway entrance from a nearly horizontal view angle.

A benchmark for anomaly detection in crowded scenes. It contains 19600 frames captured using two different cameras.

The MVTec Anomaly Detection (AD) dataset is a comprehensive real-world dataset for unsupervised anomaly detection.

The Visual Anomaly (VisA) dataset is a large-scale industrial anomaly detection dataset containing 10,821 high-resolution color images with 9,621 normal and 1,200 anomalous...

The MNIST dataset (Lecun et al., 1998), which consists of 60,000 gray-scale images of handwritten digits. Each image has an accompanying label in {0, 1,..., 9}, and is stored as...