Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image

@article{Kuo2021Patch2CADPE,
  title={Patch2CAD: Patchwise Embedding Learning for In-the-Wild Shape Retrieval from a Single Image},
  author={Weicheng Kuo and Anelia Angelova and Tsung-Yi Lin and Angela Dai},
  journal={2021 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2021},
  pages={12569-12579}
}
3D perception of object shapes from RGB image input is fundamental towards semantic scene understanding, grounding image-based perception in our spatially 3dimensional real-world environments. To achieve a mapping between image views of objects and 3D shapes, we leverage CAD model priors from existing large-scale databases, and propose a novel approach towards constructing a joint embedding space between 2D images and 3D CAD models in a patch-wise fashion – establishing correspondences between… 

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