1. 

   2D GANs Meet Unsupervised Single-View 3D Reconstruction

   Feng Liu, Xiaoming Liu

   Recent research has shown that controllable image generation based on pre-trained GANs can benefit a wide range of computer vision tasks. However, less attention has been devoted to 3D vision tasks. In light of this, we propose a novel image-conditioned neural implicit field, which can leverage 2D supervisions from GAN-generated ...

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   Keywords: 3D Shape Reconstruction, Generic Object 3D Reconstruction

2. 

   Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image

   Feng Liu, Xiaoming Liu

   Inferring 3D locations and shapes of multiple objects from a single 2D image is a long-standing objective of computer vision. Most of the existing works either predict one of these 3D properties or focus on solving both for a single object. One fundamental challenge lies in how to learn an ...

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   Keywords: 3D Object Detection, 3D Shape Reconstruction, Generic Object 3D Reconstruction

3. 

   Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction

   Feng Liu, Luan Tran, Xiaoming Liu

   Inferring 3D structure of a generic object from a 2D image is a long-standing objective of computer vision. Conventional approaches either learn completely from CAD-generated synthetic data, which have difficulty in inference from real images, or generate 2.5D depth image via intrinsic decomposition, which is limited compared to the ...

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   Keywords: Generic Object 3D Reconstruction, 3D Shape Reconstruction, Semantic Segmentation

2022

• 2D GANs Meet Unsupervised Single-View 3D Reconstruction
  Feng Liu, Xiaoming Liu
  In Proceeding of European Conference on Computer Vision (ECCV 2022), Tel-Aviv, Israel, Oct. 2022
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code
@inproceedings{ 2d-gans-meet-unsupervised-single-view-3d-reconstruction,
  author = { Feng Liu and Xiaoming Liu },
  title = { 2D GANs Meet Unsupervised Single-View 3D Reconstruction },
  booktitle = { In Proceeding of European Conference on Computer Vision },
  address = { Tel-Aviv, Israel },
  month = { October },
  year = { 2022 },
}

2021

• Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image
  Feng Liu, Xiaoming Liu
  In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), Virtual, Dec. 2021
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
@inproceedings{ voxel-based-3d-detection-and-reconstruction-of-multiple-objects-from-a-single-image,
  author = { Feng Liu and Xiaoming Liu },
  title = { Voxel-based 3D Detection and Reconstruction of Multiple Objects from a Single Image },
  booktitle = { In Proceeding of Thirty-fifth Conference on Neural Information Processing Systems },
  address = { Virtual },
  month = { December },
  year = { 2021 },
}
• Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction
  Feng Liu, Luan Tran, Xiaoming Liu
  In Proceeding of IEEE Computer Vision and Pattern Recognition (CVPR 2021), Nashville, TN, Jun. 2021
  Bibtex | PDF | arXiv | Supplemental | Project Webpage | Code | Video
@inproceedings{ fully-understanding-generic-objects-modeling-segmentation-and-reconstruction,
  author = { Feng Liu and Luan Tran and Xiaoming Liu },
  title = { Fully Understanding Generic Objects: Modeling, Segmentation, and Reconstruction },
  booktitle = { In Proceeding of IEEE Computer Vision and Pattern Recognition },
  address = { Nashville, TN },
  month = { June },
  year = { 2021 },
}