
ChronoMagic-Bench Leaderboard
Welcome to the leaderboard of the ChronoMagic-Bench! (NeurIPS 2024 D&B Spotlight)
šChronoMagic-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.
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GitHub | arXiv | Home Page | ChronoMagic-Pro | ChronoMagic-ProH
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.
U-Net | 257.56 | 1.916 | 0.478 | 81.82 | 3.13 |
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.
U-Net | 294.72 | 1.763 | 0.479 | 125.25 | 3.05 |
U-Net | 294.72 | 1.763 | 0.479 | 77.98 | 3.05 | |
DiT | 214.91 | 2.387 | 0.474 | 95.97 | 3.11 | |
DiT | 195.52 | 3.24 | 0.472 | 38.64 | 3.09 | |
U-Net | 239.31 | 2.837 | 0.47 | 70.36 | 2.62 | |
DiT | 241.09 | 2.676 | 0.448 | 75.94 | 2.57 | |
U-Net | 214.06 | 2.763 | 0.437 | 75.9 | 2.87 | |
U-Net | 244.49 | 2.282 | 0.422 | 58.08 | 3.06 | |
U-Net | 230.74 | 2.783 | 0.409 | 61.01 | 3.01 | |
U-Net | 260.61 | 2.232 | 0.403 | 94.67 | 2.29 | |
U-Net | 250.22 | 2.559 | 0.399 | 18.54 | 2.62 | |
DiT | 210.93 | 2.681 | 0.383 | 51.87 | 2.5 | |
DiT | 218.99 | 2.4 | 0.373 | 125.25 | 2.62 | |
DiT | 202.32 | 2.517 | 0.369 | 74.2 | 2.74 | |
DiT | 232.29 | 2.122 | 0.366 | 72.57 | 2.42 | |
DiT | 202.03 | 2.733 | 0.352 | 88.48 | 2.33 | |
U-Net | 210.39 | 2.714 | 0.35 | 81.32 | 2.5 | |
DiT | 187.36 | 2.758 | 0.348 | 63.88 | 3.19 | |
DiT | 223.05 | 2.317 | 0.347 | 75.98 | 2.48 | |
DiT | 228.7 | 2.459 | 0.331 | 61.5 | 2.21 | |
DiT | 216.9 | 0.972 | 0.324 | 89.76 | 1.08 | |
DiT | - | - | - | 71 | 2.64 | |
DiT | - | - | - | 48.45 | 3.36 | |
DiT | - | - | - | 28.07 | 3.76 | |
DiT | - | - | - | 121.16 | 3.18 |
Submission Guidelines
- Fill in 'Model Name' if it is your first time to submit your result or Fill in 'Revision Model Name' if you want to update your result.
- Select āBackbone Typeā (DiT or U-Net).
- Fill in your home page to 'Model Link'.
- After evaluation, follow the guidance in the github repository to obtain
ChronoMagic-Bench-Input.json
and upload it here. - Click the 'Submit Eval' button.
- Click 'Refresh' to obtain the uploaded leaderboard.