Physical Anomalous Trajectory or Motion (PHANTOM) Dataset

Last update: Dec 16, 2021

Overview

Physical Anomalous Trajectory or Motion (PHANTOM) Dataset

Description

This dataset contains the six different classes as described in our paper[]. These classes are designed to be used to detect anomalies in physical videos and are meant to be used as a benchmark to assess a method's performance on physical videos. The train set contains normal videos, the test set contains both normal and anomalous videos.

In addition, we provide a script to obtain the test and train video id's of the Something-Something V2 dataset. This too is meant to serve as even more difficult benchmark for general video anomaly detection. Our approach is decribed in the paper.

Citation

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GitHub Repository

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Physical Anomalous Trajectory or Motion (PHANTOM) Dataset

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Overview

Physical Anomalous Trajectory or Motion (PHANTOM) Dataset

Description

Citation

Owner

Data-Uncertainty Guided Multi-Phase Learning for Semi-supervised Object Detection

The codebase for our paper "Generative Occupancy Fields for 3D Surface-Aware Image Synthesis" (NeurIPS 2021)

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ISTR: End-to-End Instance Segmentation with Transformers (https://arxiv.org/abs/2105.00637)

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