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--- |
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dataset_info: |
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features: |
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- name: prompt |
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dtype: string |
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- name: prompt_asset |
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dtype: image |
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- name: video1 |
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dtype: string |
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- name: video2 |
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dtype: string |
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- name: weighted_results1_Alignment |
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dtype: float32 |
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- name: weighted_results2_Alignment |
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dtype: float32 |
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- name: detailedResults_Alignment |
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list: string |
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- name: weighted_results1_Coherence |
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dtype: float32 |
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- name: weighted_results2_Coherence |
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dtype: float32 |
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- name: detailedResults_Coherence |
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list: string |
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- name: weighted_results1_Preference |
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dtype: float32 |
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- name: weighted_results2_Preference |
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dtype: float32 |
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- name: detailedResults_Preference |
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list: string |
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- name: file_name1 |
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dtype: string |
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- name: file_name2 |
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dtype: string |
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- name: model1 |
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dtype: string |
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- name: model2 |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 318051385.0 |
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num_examples: 198 |
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download_size: 161801984 |
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dataset_size: 318051385.0 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: apache-2.0 |
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task_categories: |
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- video-classification |
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- text-to-video |
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- text-classification |
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language: |
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- en |
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tags: |
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- videos |
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- i2v |
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- image-2-video |
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- image2video |
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- image-to-video |
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- human |
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- annotations |
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- preferences |
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- likert |
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- coherence |
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- alignment |
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- style |
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- seedance |
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- seedance-1 |
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- seedance-1-pro |
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pretty_name: seedance-1-pro Human Preferences |
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size_categories: |
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- 1K<n<10K |
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--- |
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<style> |
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.vertical-container { |
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display: flex; |
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flex-direction: column; |
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gap: 60px; |
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} |
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.image-container img { |
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height: 150px; /* Set the desired height */ |
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margin:0; |
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object-fit: contain; /* Ensures the aspect ratio is maintained */ |
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width: auto; /* Adjust width automatically based on height */ |
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} |
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.image-container { |
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display: flex; /* Aligns images side by side */ |
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justify-content: space-around; /* Space them evenly */ |
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align-items: center; /* Align them vertically */ |
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} |
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.container { |
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width: 90%; |
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margin: 0 auto; |
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} |
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.text-center { |
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text-align: center; |
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display: flex; |
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align-items:center; |
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flex-direction: column; |
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} |
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.score-amount { |
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margin: 0; |
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margin-top: 10px; |
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} |
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.score-percentage { |
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font-size: 12px; |
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font-weight: semi-bold; |
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} |
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</style> |
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# Rapidata Video Generation Hailuo-02 v Marey Human Preference |
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<a href="https://www.rapidata.ai"> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/66f5624c42b853e73e0738eb/jfxR79bOztqaC6_yNNnGU.jpeg" width="300" alt="Dataset visualization"> |
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</a> |
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<a href="https://huggingface.co/datasets/Rapidata/text-2-image-Rich-Human-Feedback"> |
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</a> |
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In this dataset, ~6k human responses from ~2k human annotators were collected to evaluate Seedance 1 Pro video generation model on our benchmark. This dataset was collected in roughtly 5 min using the [Rapidata Python API](https://docs.rapidata.ai), accessible to anyone and ideal for large scale data annotation. |
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Explore our latest model rankings on our [website](https://www.rapidata.ai/benchmark). |
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If you get value from this dataset and would like to see more in the future, please consider liking it ❤️ |
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To add your own model to the benchmark send us an e-mail at: [email protected] |
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# Overview |
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In this dataset, ~6k human responses from ~2k human annotators were collected to evaluate Seedance 1 Pro video generation model on our benchmark. This dataset was collected in roughtly 5 min using the [Rapidata Python API](https://docs.rapidata.ai), accessible to anyone and ideal for large scale data annotation. |
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# Explanation of the colums |
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The dataset contains paired video comparisons. Each entry includes 'video1' and 'video2' fields, which contain links to downscaled GIFs for easy viewing. The full-resolution videos can be found [here](https://huggingface.co/datasets/Rapidata/image-to-video-human-preference-seedance-1-pro/tree/main/Videos) |
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The weighted_results column contains scores ranging from 0 to 1, representing aggregated user responses. Individual user responses can be found in the detailedResults column. |
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# Alignment |
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The alignment score quantifies how well an video matches its prompt. Users were asked: "Which video fits the description better?". |
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## Examples |
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<div class="vertical-container"> |
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<div class="container"> |
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<div class="text-center"> |
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<q>The calf moves forward, gently munching on the hay scattered on the ground.</q> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/672b7d79fd1e92e3c3567435/DXJWSH9hHv7HXxJnPI035.jpeg" width=300> |
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</div> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Score: 90.61%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/seedance-1-pro_subject-motion_0039.gif" width=500> |
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</div> |
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<div> |
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<h3 class="score-amount">Hailuo-02 </h3> |
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<div class="score-percentage">(Score: 9.39%)</div> |
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<img src="https://assets.rapidata.ai/hailuo-02_subject-motion_0039.gif" width=500> |
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</div> |
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</div> |
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</div> |
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<div class="container"> |
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<div class="text-center"> |
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<q>The fern slowly unfurls as a gentle breeze causes it to sway softly.</q> |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/672b7d79fd1e92e3c3567435/n1nLh_PI_TxqbvsH9C6FT.jpeg" width=300> |
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</div> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Score: 15.68%)</div> |
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<img src="https://assets.rapidata.ai/seedance-1-pro_scene-motion_0060.gif" width=500> |
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</div> |
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<div> |
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<h3 class="score-amount">Hailuo-02 </h3> |
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<div class="score-percentage">(Score: 84.32%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/hailuo-02_scene-motion_0060.gif" width=500> |
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</div> |
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</div> |
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</div> |
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</div> |
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# Coherence |
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The coherence score measures whether the generated video is logically consistent and free from artifacts or visual glitches. Without seeing the original prompt, users were asked: "Which video has more glitches and is more likely to be AI generated?" |
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## Examples |
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<div class="vertical-container"> |
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<div class="container"> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Glitch Rating: 8.78%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/seedance-1-pro_style_0047.gif" width="500" alt="Dataset visualization"> |
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</div> |
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<div> |
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<h3 class="score-amount">Marey </h3> |
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<div class="score-percentage">(Glitch Rating: 91.22%)</div> |
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<img src="https://assets.rapidata.ai/marey_0047.gif" width="500" alt="Dataset visualization"> |
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</div> |
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</div> |
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</div> |
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<div class="container"> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Glitch Rating: 80%)</div> |
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<img src="https://assets.rapidata.ai/seedance-1-pro_style_0007.gif" width="500" alt="Dataset visualization"> |
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</div> |
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<div> |
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<h3 class="score-amount">Hailuo-02 </h3> |
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<div class="score-percentage">(Glitch Rating: 20%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/hailuo-02_style_0007.gif" width="500" alt="Dataset visualization"> |
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</div> |
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</div> |
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</div> |
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</div> |
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# Preference |
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The preference score reflects how visually appealing participants found each video, independent of the prompt. Users were asked: "Which video do you prefer aesthetically?" |
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## Examples |
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<div class="vertical-container"> |
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<div class="container"> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Score: 90.74%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/seedance-1-pro_style_0083.gif" width="500" alt="Dataset visualization"> |
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</div> |
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<div> |
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<h3 class="score-amount">Marey </h3> |
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<div class="score-percentage">(Score: 9.26%)</div> |
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<img src="https://assets.rapidata.ai/marey_0083.gif" width="500" alt="Dataset visualization"> |
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</div> |
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</div> |
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</div> |
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<div class="container"> |
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<div class="image-container"> |
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<div> |
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<h3 class="score-amount">Seedance 1 Pro </h3> |
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<div class="score-percentage">(Score: 9.03%)</div> |
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<img src="https://assets.rapidata.ai/seedance-1-pro_subject-motion_0036.gif" width="500" alt="Dataset visualization"> |
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</div> |
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<div> |
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<h3 class="score-amount">Hailuo-02 </h3> |
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<div class="score-percentage">(Score: 90.97%)</div> |
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<img style="border: 5px solid #18c54f;" src="https://assets.rapidata.ai/hailuo-02_subject-motion_0036.gif " width="500" alt="Dataset visualization"> |
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</div> |
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</div> |
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</div> |
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</div> |
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</br> |
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# About Rapidata |
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Rapidata's technology makes collecting human feedback at scale faster and more accessible than ever before. Visit [rapidata.ai](https://www.rapidata.ai/) to learn more about how we're revolutionizing human feedback collection for AI development. |
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# Other Datasets |
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We run a benchmark of the major video generation models, the results can be found on our [website](https://www.rapidata.ai/leaderboard/video-models). We rank the models according to their coherence/plausiblity, their aligment with the given prompt and style prefernce. The underlying 2M+ annotations can be found here: |
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- Link to the [Rich Video Annotation dataset](https://huggingface.co/datasets/Rapidata/text-2-video-Rich-Human-Feedback) |
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- Link to the [Coherence dataset](https://huggingface.co/datasets/Rapidata/Flux_SD3_MJ_Dalle_Human_Coherence_Dataset) |
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- Link to the [Text-2-Image Alignment dataset](https://huggingface.co/datasets/Rapidata/Flux_SD3_MJ_Dalle_Human_Alignment_Dataset) |
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- Link to the [Preference dataset](https://huggingface.co/datasets/Rapidata/700k_Human_Preference_Dataset_FLUX_SD3_MJ_DALLE3) |
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