| --- |
| license: mit |
| language: |
| - en |
| pretty_name: HPDv3 |
| size_categories: |
| - 1M<n<10M |
| --- |
| <div align="center"> |
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| # 🎯 HPSv3: Towards Wid-Spectrum Human Preference Score (ICCV 2025) |
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| [](https://research.nvidia.com/labs/par/addit/) |
| [](https://arxiv.org/abs/2508.03789) |
| [](https://arxiv.org/abs/2508.03789) |
| [](https://huggingface.co/MizzenAI/HPSv3) |
| [](https://github.com/MizzenAI/HPSv3) |
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| **Yuhang Ma**<sup>1,3*</sup>  **Yunhao Shui**<sup>1,4*</sup>  **Xiaoshi Wu**<sup>2</sup>  **Keqiang Sun**<sup>1,2†</sup>  **Hongsheng Li**<sup>2,5,6†</sup> |
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| <sup>1</sup>Mizzen AI   <sup>2</sup>CUHK MMLab   <sup>3</sup>King’s College London   <sup>4</sup>Shanghai Jiaotong University   <sup>5</sup>Shanghai AI Laboratory   <sup>6</sup>CPII, InnoHK   |
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| <sup>*</sup>Equal Contribution  <sup>†</sup>Equal Advising |
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| </div> |
| |
| <p align="center"> |
| <img src="assets/teaser.png" alt="Teaser" width="900"/> |
| </p> |
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| |
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| # Human Preference Dataset v3 |
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| Human Preference Dataset v3 (HPD v3) comprises **1.08M** text-image pairs and **1.17M** annotated pairwise data. To modeling the wide spectrum of human preference, we introduce newest state-of-the-art generative models and high quality real photographs while maintaining old models and lower quality real images. |
| |
| |
| ## How to Use |
| ```bash |
| cat images.tar.gz.* | gunzip | tar -xv |
| ``` |
| |
| ## Detail information of HPDv3 |
| |
| | Image Source | Type | Num Image | Prompt Source | Split | |
| |--------------|------|-----------|---------------|-------| |
| | High Quality Image (HQI) | Real Image | 57759 | VLM Caption | Train & Test | |
| | MidJourney | - | 331955 | User | Train | |
| | CogView4 | DiT | 400 | HQI+HPDv2+JourneyDB | Test | |
| | FLUX.1 dev | DiT | 48927 | HQI+HPDv2+JourneyDB | Train & Test | |
| | Infinity | Autoregressive | 27061 | HQI+HPDv2+JourneyDB | Train & Test | |
| | Kolors | DiT | 49705 | HQI+HPDv2+JourneyDB | Train & Test | |
| | HunyuanDiT | DiT | 46133 | HQI+HPDv2+JourneyDB | Train & Test | |
| | Stable Diffusion 3 Medium | DiT | 49266 | HQI+HPDv2+JourneyDB | Train & Test | |
| | Stable Diffusion XL | Diffusion | 49025 | HQI+HPDv2+JourneyDB | Train & Test | |
| | Pixart Sigma | Diffusion | 400 | HQI+HPDv2+JourneyDB | Test | |
| | Stable Diffusion 2 | Diffusion | 19124 | HQI+JourneyDB | Train & Test | |
| | CogView2 | Autoregressive | 3823 | HQI+JourneyDB | Train & Test | |
| | FuseDream | Diffusion | 468 | HQI+JourneyDB | Train & Test | |
| | VQ-Diffusion | Diffusion | 18837 | HQI+JourneyDB | Train & Test | |
| | Glide | Diffusion | 19989 | HQI+JourneyDB | Train & Test | |
| | Stable Diffusion 1.4 | Diffusion | 18596 | HQI+JourneyDB | Train & Test | |
| | Stable Diffusion 1.1 | Diffusion | 19043 | HQI+JourneyDB | Train & Test | |
| | Curated HPDv2 | - | 327763 | - | Train | |
| |
| |
| ## Dataset Visualization |
| <p align="left"> |
| <img src="assets/datasetvisual_0.jpg" alt="Dataset" width="900"/> |
| </p> |
| |
| |
| ## Dataset Structure |
| |
| ### All Annotated Pairs (`all.json`) |
| |
| **Important Notes: In HPDv3, we simply put the preferred sample at the first place (path1)** |
| |
| `all.json` contains **all** annotated pairs except for test. There are three types of training samples in the json file. |
| |
| ```json |
| [ |
| // samples from HPDv3 annotation pipeline |
| { |
| "prompt": "Description of the visual content or the generation prompt.", |
| "choice_dist": [12, 7], // Distribution of votes from annotators (12 votes for image1, 7 votes for image2) |
| "confidence": 0.9999907, // Confidence score reflecting preference reliability, based on annotators' capabilities (independent of choice_dist) |
| "path1": "images/uuid1.jpg", // File path to the preferred image |
| "path2": "images/uuid2.jpg", // File path to the non-preferred image |
| "model1": "flux", // Model used to generate the preferred image (path1) |
| "model2": "infinity" // Model used to generate the non-preferred image (path2) |
| }, |
| // samples from Midjourney |
| { |
| "prompt": "Description of the visual content or the generation prompt.", |
| "choice_dist": null, // No distribution of votes Information from Discord |
| "confidence": null, // No Confidence Information from Discord |
| "path1": "images/uuid1.jpg", // File path to the preferred image. |
| "path2": "images/uuid2.jpg", // File path to the non-preferred image. |
| "model1": "midjourney", // Comparsion between images generated from midjourney |
| "model2": "midjourney" // Comparsion between images generated from midjourney |
| }, |
| // samples from Curated HPDv2 |
| { |
| "prompt": "Description of the visual content or the generation prompt.", |
| "choice_dist": null, // No distribution of votes Information from the original HPDv2 traindataset |
| "confidence": null, // No Confidence Information from the original HPDv2 traindataset |
| "path1": "images/uuid1.jpg", // File path to the preferred image. |
| "path2": "images/uuid2.jpg", // File path to the non-preferred image. |
| "model1": "hpdv2", // No specific model name in the original HPDv2 traindataset, set to hpdv2 |
| "model2": "hpdv2" // No specific model name in the original HPDv2 traindataset, set to hpdv2 |
| }, |
| ... |
| ] |
| ``` |
| |
| ### Train set (`train.json`) |
| We sample part of training data from `all.json` to build training dataset `train.json`. Moreover, to improve robustness, we integrate random sampled part of data from [Pick-a-pic](https://huggingface.co/datasets/pickapic-anonymous/pickapic_v1) and [ImageRewardDB](https://huggingface.co/datasets/zai-org/ImageRewardDB), which is `pickapic.json` and `imagereward.json`. For these two datasets, we only provide the pair infomation, and its corresponding image can be found in their official dataset repository. |
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|
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| ### Test Set (`test.json`) |
| ```json |
| [ |
| { |
| "prompt": "Description of the visual content", |
| "path1": "images/uuid1.jpg", // Preferred sample |
| "path2": "images/uuid2.jpg", // Unpreferred sample |
| "model1": "flux", //Model used to generate the preferred sample (path1). |
| "model2": "infinity", //Model used to generate the non-preferred sample (path2). |
| |
| }, |
| ... |
| ] |
| ``` |