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---
task_categories:
- visual-question-answering
language:
- en
size_categories:
- 1K<n<10K
license: mit
---
# Towards Event-oriented Long Video Understanding
<font size=3><div align='center'> [[📖 arXiv Paper]()]</div>
---
## 👀 Overview
We introduce **Event-Bench**, an event-oriented long video understanding benchmark built on existing datasets and human annotations. **Event-Bench** consists of three event understanding abilities and six event-related tasks, including 2,190 test instances to comprehensively evaluate the ability to understand video events.
<p align="center">
<img src="./asset/fig_benchmark.jpg" width="100%" height="100%">
</p>
**Event-Bench** provides a systematic comparison across different kinds of capabilities for existing video MLLMs, and points out the major shortcomings of open-source MLLMs.
## 🔍 Dataset
Download the raw videos in VNBench from the [google drive link](https://drive.google.com/file/d/1wjjH2dK-KpaObFdS1yc-TBUTCvXsaLwc/view?usp=sharing).
**License**:
```
Event-Bench is only used for academic research. Commercial use in any form is prohibited.
```
## 🔮 Evaluation Pipeline
Please refer to https://github.com/RUCAIBox/Event-Bench
## 📈 Experimental Results
- **Evaluation results of different Video MLLMs.**
<p align="center">
<img src="./asset/performance.png" width="96%" height="50%">
</p>
## Citation
If you find our work helpful for your research, please consider citing our work.
```bibtex
```
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