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  "license": "Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)",
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  "citation": {
    "title": "HanDrawer: Leveraging Spatial Information to Render Realistic Hands Using a Conditional Diffusion Model in Single Stage",
    "arxiv_id": "2503.02127",
    "doi": "10.48550/arXiv.2503.02127",
    "url": "https://arxiv.org/abs/2503.02127"
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  "source_dataset_references": [
    {
      "name": "DexYCB",
      "status_in_current_release": "included via the DexYCB-derived MANUS test split",
      "bibtex_key": "chao2021dexycb",
      "citation": {
        "title": "DexYCB: A benchmark for capturing hand grasping of objects",
        "authors": "Yu-Wei Chao, Wei Yang, Yu Xiang, Pavlo Molchanov, Ankur Handa, Jonathan Tremblay, Yashraj S. Narang, Karl Van Wyk, Umar Iqbal, Stan Birchfield, and others",
        "venue": "Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition",
        "pages": "9044--9053",
        "year": 2021
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}