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README.md
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pretty_name: X-Capture
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#
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The X-Capture dataset contains multisensory data collected from **600 real-world objects** in **nine in-the-wild environments**. We provide **RGB-D, acoustic, tactile,** and **3D data**. Each object has six recorded points each, covering diverse locations on the object.
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### Dataset Description
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- **Download:** https://huggingface.co/datasets/swistreich/XCapture/resolve/main/XCapture_data.zip
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---
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##
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- Cross-sensory retrieval (audio→image, touch→3D, etc.)
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- Multimodal representation learning
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- Pretraining encoders across RGB-D / tactile / audio
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## Dataset Structure
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Each object directory contains six capture points:
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object_id/
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point_id/
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*_rgb.png
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*_depth.png
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*_10N_tactile.png
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scp.mp4 # impact audio
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- **rgb:** 640×480 color images
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- **depth:** aligned depth images
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- **tactile:** high-resolution
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- **audio:** ~
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- **3D:** object mesh
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There are no train/val/test splits; users are encouraged to construct splits suited to their task.
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pretty_name: X-Capture
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# X-Capture: An Open-Source Portable Device for Multi-Sensory Learning (ICCV 2025)
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**Authors:** Samuel Clarke, Suzannah Wistreich, Yanjie Ze, Jiajun Wu
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Stanford University
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[[Paper]](https://arxiv.org/abs/2504.02318) | [[Project Page]](https://xcapture.github.io) | [[Dataset Download]](https://huggingface.co/datasets/swistreich/XCapture/resolve/main/XCapture_data.zip)
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The X-Capture dataset contains multisensory data collected from **600 real-world objects** in **nine in-the-wild environments**. We provide **RGB-D, acoustic, tactile,** and **3D data**. Each object has six recorded points each, covering diverse locations on the object.
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### Dataset Description
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- **Download:** https://huggingface.co/datasets/swistreich/XCapture/resolve/main/XCapture_data.zip
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---
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## Usage
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- Cross-sensory retrieval (audio→image, touch→3D, etc.)
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- Multimodal representation learning
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- Pretraining encoders across RGB-D / tactile / audio
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## Dataset Structure
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Each object directory contains six capture points, each with:
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- **rgb:** 640×480 color images
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- **depth:** aligned depth images
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- **tactile:** high-resolution DIGIT tactile images under 10N, 15N, 20N presses
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- **audio:** ~3s audio/video clip of impact sound
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- **3D:** local object mesh at contact point
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There are no train/val/test splits; users are encouraged to construct splits suited to their task.
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