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<a href="https://csu-jpg.github.io/FlowInOne.github.io/" style="text-decoration: none;">🌐 Homepage</a> |
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<a href="https://github.com/CSU-JPG/FlowInOne" style="text-decoration: none;">💻 Code</a> |
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<a href="https://arxiv.org" style="text-decoration: none;">📄 Paper</a> |
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<a href="https://huggingface.co/datasets/CSU-JPG/VisPrompt5M" style="text-decoration: none;">📁 Dataset</a> |
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<a href="https://huggingface.co/datasets/CSU-JPG/VPBench" style="text-decoration: none;">🌏 Benchmark</a> |
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<a href="https://huggingface.co/CSU-JPG/FlowInOne" style="text-decoration: none;">🤗 Model</a>
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## Evaluation
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Our evaluation scripts are now available on [GitHub](https://github.com/CSU-JPG/FlowInOne)!
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<h2 align="center" style="margin-top: 0; margin-bottom: 15px;">
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<span style="color:#0052CC">F</span><span style="color:#135FD0">l</span><span style="color:#266CD4">o</span><span style="color:#3979D7">w</span><span style="color:#4C86DB">I</span><span style="color:#6093DF">n</span><span style="color:#73A0E3">O</span><span style="color:#86ADE7">n</span><span style="color:#99BAEB">e</span>: Unifying Multimodal Generation as
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<span style="color:#0052CC">I</span><span style="color:#0958CE">m</span><span style="color:#125ED0">a</span><span style="color:#1B64D2">g</span><span style="color:#246AD4">e</span><span style="color:#2D70D6">-</span><span style="color:#3676D8">i</span><span style="color:#3F7CDA">n</span><span style="color:#4882DC">,</span> <span style="color:#5188DE">I</span><span style="color:#5A8EE0">m</span><span style="color:#6394E2">a</span><span style="color:#6C9AE4">g</span><span style="color:#75A0E6">e</span><span style="color:#7EA6E8">-</span><span style="color:#87ACEA">o</span><span style="color:#90B2EC">u</span><span style="color:#99B8EE">t</span> Flow Matching
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</h2>
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<p align="center" style="font-size: 15px;">
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<span style="color:#E74C3C; font-weight: bold;">TL;DR:</span> <strong>The first vision-centric image-in, image-out image generation model.</strong>
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</p>
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<p align="center" style="font-size: 16px;">
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<a href="https://csu-jpg.github.io/FlowInOne.github.io/" style="text-decoration: none;">🌐 Homepage</a> |
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<a href="https://github.com/CSU-JPG/FlowInOne" style="text-decoration: none;">💻 Code</a> |
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<a href="https://arxiv.org" style="text-decoration: none;">📄 Paper</a> |
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<a href="https://huggingface.co/datasets/CSU-JPG/VisPrompt5M" style="text-decoration: none;">📁 Dataset</a> |
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<a href="https://huggingface.co/datasets/CSU-JPG/VPBench" style="text-decoration: none;">🌏 Benchmark</a> |
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<a href="https://huggingface.co/CSU-JPG/FlowInOne" style="text-decoration: none;">🤗 Model</a>
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</p>
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# VP-Bench
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**VP-Bench** is the official evaluation benchmark for [**FlowInOne**](https://csu-jpg.github.io/FlowInOne.github.io/).
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It is a rigorously curated benchmark assessing **instruction faithfulness**, **spatial precision**, **visual realism**, and **content consistency** across eight distinct visual prompting tasks.
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## Evaluation
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Our evaluation scripts are now available on [GitHub](https://github.com/CSU-JPG/FlowInOne)!
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