|
MODEL_INFO = ["Model", "Backbone"] |
|
|
|
ALL_RESULTS = ["UMT-FVD↓", "UMTScore↑", "MTScore↑", "CHScore↑", "GPT4o-MTScore↑"] |
|
|
|
SELECTED_RESULTS = ["UMT-FVD↓", "UMTScore↑", "MTScore↑", "CHScore↑", "GPT4o-MTScore↑"] |
|
SELECTED_RESULTS_150 = ["UMT-FVD↓", "UMTScore↑", "MTScore↑", "GPT4o-MTScore↑"] |
|
|
|
DATA_TITILE_TYPE = ["markdown", 'markdown', "number", "number", "number", "number", "number"] |
|
|
|
CSV_DIR_CHRONOMAGIC_BENCH = "./file/results_ChronoMagic-Bench.csv" |
|
CSV_DIR_CHRONOMAGIC_BENCH_150 = "./file/results_ChronoMagic-Bench-150.csv" |
|
|
|
COLUMN_NAMES = MODEL_INFO + ALL_RESULTS |
|
|
|
LEADERBORAD_INTRODUCTION = """ |
|
<div style='display: flex; align-items: center; justify-content: center; text-align: center;'> |
|
<img src='https://www.pnglog.com/MqiNJ0.jpg' style='width: 600px; height: auto; margin-right: 10px;' /> |
|
</div> |
|
|
|
# ChronoMagic-Bench Leaderboard |
|
|
|
Welcome to the leaderboard of the ChronoMagic-Bench! |
|
|
|
🏆ChronoMagic-Bench represents the inaugural benchmark dedicated to assessing T2V models' capabilities in generating time-lapse videos that demonstrate significant metamorphic amplitude and temporal coherence. The benchmark probes T2V models for their physics, biology, and chemistry capabilities, in a free-form text control. |
|
|
|
If you like our project, please give us a star ⭐ on GitHub for the latest update. |
|
|
|
[GitHub](https://github.com/PKU-YuanGroup/ChronoMagic-Bench) | [arXiv](https://arxiv.org/abs/2406.18522) | [Home Page](https://pku-yuangroup.github.io/ChronoMagic-Bench/) | [ChronoMagic-Pro](https://huggingface.co/datasets/BestWishYsh/ChronoMagic-Pro) | [ChronoMagic-ProH](https://huggingface.co/datasets/BestWishYsh/ChronoMagic-ProH) |
|
""" |
|
|
|
SUBMIT_INTRODUCTION = """# Submit Introduction |
|
Obtain `ChronoMagic-Bench-Input.json` from our [github repository](https://github.com/PKU-YuanGroup/ChronoMagic-Bench) after evaluation. |
|
|
|
|
|
## Submit Example |
|
For example, if you want to upload Video-ChatGPT's result in the leaderboard, you need to: |
|
1. Fill in 'MagicTime' in 'Model Name' if it is your first time to submit your result (You can leave 'Revision Model Name' blank). |
|
2. Fill in 'MagicTime' in 'Revision Model Name' if you want to update your result (You can leave 'Model Name' blank). |
|
3. Select ‘Backbone Type’ (DiT or U-Net). |
|
4. Fill in 'https://github.com/x/x' in 'Model Link'. |
|
5. Upload `ChronoMagic-Bench-Input.json`. |
|
6. Click the 'Submit Eval' button. |
|
7. Click 'Refresh' to obtain the uploaded leaderboard. |
|
""" |
|
|
|
TABLE_INTRODUCTION = """In the table below, we summarize each task performance of all the models. |
|
We use UMT-FVD, UMTScore, MTScore, CHScore, GPT4o-MTScore as the primary evaluation metric for each tasks. |
|
""" |
|
|
|
CITATION_BUTTON_LABEL = "Copy the following snippet to cite these results" |
|
CITATION_BUTTON_TEXT = r"""@article{yuan2024magictime, |
|
title={MagicTime: Time-lapse Video Generation Models as Metamorphic Simulators}, |
|
author={Yuan, Shenghai and Huang, Jinfa and Shi, Yujun and Xu, Yongqi and Zhu, Ruijie and Lin, Bin and Cheng, Xinhua and Yuan, Li and Luo, Jiebo}, |
|
journal={arXiv preprint arXiv:2404.05014}, |
|
year={2024} |
|
}""" |
|
|