Rahima411/ucf-anomaly-detection-mapped

UCF-Crime: Precomputed I3D Features with Temporal Annotations

This dataset provides pre-extracted 1024-dimensional I3D RGB features along with frame-level temporal anomaly labels for videos from the UCF-Crime dataset.

Dataset Characteristics

Features

• —1024-dimensional I3D RGB feature vectors
• —Extracted from 64 uniformly sampled frames per video
• —Feature tensor shape: [64, 1024]

Temporal Annotations

• —Mapped from original anomaly intervals
• —Re-scaled to match the 64 sampled frames
• —Only videos with valid annotations are included

Coverage

• —Videos that contain complete temporal anomaly intervals
• —Suitable for supervised learning tasks

Recommended Usage

This dataset is ideal for:

• —Frame-level binary classification
• —Reconstruction-based anomaly detection
• —Temporal convolutional networks (TCN)
• —Transformer-based sequence models
• —Sequential anomaly scoring models

Since features are already extracted, experiments are lightweight and GPU-efficient.

Loading the Dataset

The Data Loader code has also been provided. Please refer to that.

Citation

@inproceedings{sultani2018real, title={Real-world Anomaly Detection in Surveillance Videos}, author={Sultani, Waqas and Chen, Chen and Shah, Mubarak}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, pages={4469--4478}, year={2018} }