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--- |
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title: Open VLM Video Leaderboard |
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emoji: 🌎 |
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colorFrom: blue |
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colorTo: green |
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sdk: gradio |
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sdk_version: 4.44.0 |
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app_file: app.py |
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pinned: true |
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license: apache-2.0 |
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tags: |
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- leaderboard |
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short_description: 'VLMEvalKit Eval Results in video understanding benchmark' |
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--- |
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In this leaderboard, we show the results of all video understanding metrics obtained using VLMEvalKit. The space provides an overall leaderboard with carefully selected benchmarks and total scores; And benchmarking leaderboards that provide overall and fine-grained scores for each video understanding benchmark. |
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Github: https://github.com/open-compass/VLMEvalKit |
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Report: https://arxiv.org/abs/2407.11691 |
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Please consider to cite the report if the resource is useful to your research: |
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```BibTex |
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@misc{duan2024vlmevalkitopensourcetoolkitevaluating, |
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title={VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models}, |
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author={Haodong Duan and Junming Yang and Yuxuan Qiao and Xinyu Fang and Lin Chen and Yuan Liu and Amit Agarwal and Zhe Chen and Mo Li and Yubo Ma and Hailong Sun and Xiangyu Zhao and Junbo Cui and Xiaoyi Dong and Yuhang Zang and Pan Zhang and Jiaqi Wang and Dahua Lin and Kai Chen}, |
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year={2024}, |
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eprint={2407.11691}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CV}, |
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url={https://arxiv.org/abs/2407.11691}, |
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} |
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``` |
