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ShapeR introduces a novel approach to metric shape generation. Given an input image sequence, preprocessing extracts per-object metric sparse SLAM points, images, poses, and captions using off-the-shelf methods. A rectified flow transformer operating on VecSet latents conditions on these multimodal inputs to generate a shape code, which is decoded into the object’s mesh. By applying the model object-centrically to each detected object, we obtain a metric reconstruction of the entire scene.
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[Project Page](http://facebookresearch.github.io/ShapeR) | [Paper](resources/ShapeR.pdf) | [Video](https://www.youtube.com/watch?v=EbY30KAA55I) | [HF-Model](https://huggingface.co/facebook/ShapeR/) | [HF Evaluation Dataset](https://huggingface.co/datasets/facebook/ShapeR-Evaluation)
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## Usage
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ShapeR introduces a novel approach to metric shape generation. Given an input image sequence, preprocessing extracts per-object metric sparse SLAM points, images, poses, and captions using off-the-shelf methods. A rectified flow transformer operating on VecSet latents conditions on these multimodal inputs to generate a shape code, which is decoded into the object’s mesh. By applying the model object-centrically to each detected object, we obtain a metric reconstruction of the entire scene.
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[Project Page](http://facebookresearch.github.io/ShapeR) | [Paper](https://cdn.jsdelivr.net/gh/facebookresearch/ShapeR@main/resources/ShapeR.pdf) | [Video](https://www.youtube.com/watch?v=EbY30KAA55I) | [HF-Model](https://huggingface.co/facebook/ShapeR/) | [HF Evaluation Dataset](https://huggingface.co/datasets/facebook/ShapeR-Evaluation)
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## Usage
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