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[NeurIPS’23] A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and Causal Relationship

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VideoCube Python Toolkit

This repository contains the official python toolkit for running experiments and evaluate performance on VideoCube benchmark. The code is written in pure python and is compile-free.

VideoCube is a high-quality and large-scale benchmark to create a challenging real-world experimental environment for Global Instance Tracking (GIT) task.

Installation

Clone the repository and install dependencies:

git clone https://github.com/huuuuusy/videocube-toolkit.git
pip install -r requirements.txt

A Concise Example

test-videocube.py is a simple example on how to use the toolkit to define a tracker, run experiments on VideoCube and evaluate performance.

The more detailed introduction will be uploaded soon.

Issues

Please report any problems or suggessions in the Issues page.

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[NeurIPS’23] A Multi-modal Global Instance Tracking Benchmark (MGIT): Better Locating Target in Complex Spatio-temporal and Causal Relationship

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