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.

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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

A general framework for inferring CNNs efficiently. Reduce the inference latency of MobileNet-V3 by 1.3x on an iPhone XS Max without sacrificing accuracy.

Google Landmark Recogntion and Retrieval 2021 Solutions

Cl datasets - PyTorch image dataloaders and utility functions to load datasets for supervised continual learning

Code for the paper Language as a Cognitive Tool to Imagine Goals in Curiosity Driven Exploration

Unsupervised Image-to-Image Translation

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