Video Anomaly Detection - Groups

LDPolypVideo Benchmark

A large-scale colonoscopy video dataset containing diverse polyps.

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Hyperkvasir and LDPolypVideo

A large-scale colonoscopy video dataset containing 61 normal videos and 102 abnormal videos for training, and 30 normal videos and 60 abnormal videos for testing.

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Real-world anomaly detection in surveillance videos

Real-world anomaly detection in surveillance videos.

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Point Cloud Video Anomaly Detection Based on Point Spatio-Temporal Auto-Encoder

Video anomaly detection has great potential in enhancing safety in the production and monitoring of crucial areas. Currently, most video anomaly detection methods are based on...

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Abnormal Event Detection at 150 FPS in MATLAB

Abnormal Event Detection at 150 FPS in MATLAB dataset

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Street Scene

A new large-scale dataset for video anomaly detection, Street Scene, contains 46 training video sequences and 35 testing video sequences taken from a static USB camera looking...

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UCSD Ped1 & Ped2

UCSD Ped1 & Ped2 dataset for single-scene video anomaly detection

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Multimodal Motion Conditioned Diffusion Model for Skeleton-based Video Anomal...

Anomalies are rare and anomaly detection is often therefore framed as One-Class Classification (OCC), i.e. trained solely on normalcy. Leading OCC techniques constrain the...

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UCF-Crime and XD-Violence datasets

The UCF-Crime and XD-Violence datasets are used for weakly supervised video anomaly detection.

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Object-centric auto-encoders and dummy anomalies for abnormal event detection...

Object-centric auto-encoders and dummy anomalies for abnormal event detection in video.

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Clustering driven deep autoencoder for video anomaly detection

Clustering driven deep autoencoder for video anomaly detection.

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Learning Not to Reconstruct Anomalies

Video anomaly detection is often seen as one-class classiﬁcation (OCC) problem due to the limited availability of anomaly examples.

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CUHK Avenue dataset

A benchmark dataset for anomaly detection in videos

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Video Anomaly Detection by Estimating Likelihood of Representations

Video anomaly detection is a challenging task not only because it involves solving many sub-tasks such as motion representation, object localization and action recognition, but...

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UBnormal

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....

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Avenue

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

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Ped2

The Ped2 dataset comprises of 16 training and 12 test videos and all videos have the same scene in the background.

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Video Anomaly Detection via Spatio-Temporal Pseudo-Anomaly Generation

Video Anomaly Detection (VAD) is an open-set recognition task, which is usually formulated as a one-class classification (OCC) problem, where training data is comprised of...

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ShanghaiTech

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

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CUHK Avenue

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.

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22 datasets found