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[HKUST](https://hkust.edu.hk/)<sup>1</sup>, [Horizon Robotics](https://en.horizon.auto/)<sup>2</sup>, [CUHK](https://cuhk.edu.hk/)<sup>3</sup>, [NJU](https://www.nju.edu.cn/)<sup>4</sup><br>
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<sup>*</sup> Corresponding Author, <sup>§</sup> Project Leader
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<br><br><image src='assets/teaser.png'/>
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</div>
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## 🚀News
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- ```[August 2025]``` Achieve SOTA at paperwithcode leaderboards: Image Reconstruction on ImageNet and UHDBench. <image src='assets/SOTA_recon_fid_imagenet_badge.jpg'/> <image src='assets/SOTA_recon_PSNR_UHD_badge.jpg'/>
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- ```[August 2025]``` Released Inference Code
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- ```[August 2025]``` Released [model zoo](https://huggingface.co/mkjia/MGVQ/tree/main).
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- ```[August 2025]``` Released dataset for ultra-high-definition image reconstruction evaluation. Our proposed super-resolution image reconstruction [UHDBench dataset](https://huggingface.co/datasets/mkjia/UHDBench/tree/main) is released.
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## 🗄️Demos
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- 🔥 Qualitative reconstruction images with $16$ x downsampling on $2560$ x $1440$ UHDBench dataset.
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<image src='assets/qual_recon.png'/>
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- 🔥 Qualitative class-to-image generation of Imagenet. The classes are dog(Golden Retriever and Husky), cliff, and bald eagle.
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<image src='assets/qual_gen.png'/>
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- 🔥 Reconstruction evaluation on 256×256 ImageNet benchmark.
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<image src='assets/recon_tab_1.jpg'/>
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- 🔥 Zero-shot reconstruction evaluation with a downsample ratio of 16 on 512×512 datasets.
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<image src='assets/recon_tab_2.jpg'/>
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- 🔥 Zero-shot reconstruction evaluation with a downsample ratio of 16 on 2560×1440 datasets.
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<div align="center"><image src='assets/recon_tab_3.jpg'/></image></div>
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## 🗄️Demos
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[HKUST](https://hkust.edu.hk/)<sup>1</sup>, [Horizon Robotics](https://en.horizon.auto/)<sup>2</sup>, [CUHK](https://cuhk.edu.hk/)<sup>3</sup>, [NJU](https://www.nju.edu.cn/)<sup>4</sup><br>
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<sup>*</sup> Corresponding Author, <sup>§</sup> Project Leader
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<br><br><image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/teaser.png'/>
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</div>
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## 🚀News
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- ```[August 2025]``` Achieve SOTA at paperwithcode leaderboards: Image Reconstruction on ImageNet and UHDBench. <image src='https://huggingface.co/mkjia/MGVQ/raw/main/assets/SOTA_recon_fid_imagenet_badge.jpg'/> <image src='https://huggingface.co/mkjia/MGVQ/raw/main/assets/SOTA_recon_PSNR_UHD_badge.jpg'/>
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- ```[August 2025]``` Released Inference Code
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- ```[August 2025]``` Released [model zoo](https://huggingface.co/mkjia/MGVQ/tree/main).
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- ```[August 2025]``` Released dataset for ultra-high-definition image reconstruction evaluation. Our proposed super-resolution image reconstruction [UHDBench dataset](https://huggingface.co/datasets/mkjia/UHDBench/tree/main) is released.
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## 🗄️Demos
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- 🔥 Qualitative reconstruction images with $16$ x downsampling on $2560$ x $1440$ UHDBench dataset.
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<image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/qual_recon.png'/>
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- 🔥 Qualitative class-to-image generation of Imagenet. The classes are dog(Golden Retriever and Husky), cliff, and bald eagle.
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<image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/qual_gen.png'/>
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- 🔥 Reconstruction evaluation on 256×256 ImageNet benchmark.
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<image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/recon_tab_1.jpg'/>
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- 🔥 Zero-shot reconstruction evaluation with a downsample ratio of 16 on 512×512 datasets.
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<image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/recon_tab_2.jpg'/>
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- 🔥 Zero-shot reconstruction evaluation with a downsample ratio of 16 on 2560×1440 datasets.
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<div align="center"><image src='https://huggingface.co/mkjia/MGVQ/resolve/main/assets/recon_tab_3.jpg'/></image></div>
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## 🗄️Demos
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