UprightNet: Geometry-Aware Camera Orientation Estimation From Single Images

@article{Xian2019UprightNetGC,
  title={UprightNet: Geometry-Aware Camera Orientation Estimation From Single Images},
  author={Wenqi Xian and Z. Li and Matthew Fisher and J. Eisenmann and E. Shechtman and Noah Snavely},
  journal={2019 IEEE/CVF International Conference on Computer Vision (ICCV)},
  year={2019},
  pages={9973-9982}
}
  • Wenqi Xian, Z. Li, +3 authors Noah Snavely
  • Published 2019
  • Computer Science
  • 2019 IEEE/CVF International Conference on Computer Vision (ICCV)
  • We introduce UprightNet, a learning-based approach for estimating 2DoF camera orientation from a single RGB image of an indoor scene. [...] Key Method In particular, we design a network that predicts two representations of scene geometry, in both the local camera and global reference coordinate systems, and solves for the camera orientation as the rotation that best aligns these two predictions via a differentiable least squares module.Expand Abstract
    In-Plane Rotation-Aware Monocular Depth Estimation Using SLAM
    3
    Neural Geometric Parser for Single Image Camera Calibration
    Height and Uprightness Invariance for 3D Prediction From a Single View
    Surface Normal Estimation of Tilted Images via Spatial Rectifier
    1
    VPLNet: Deep Single View Normal Estimation With Vanishing Points and Lines
    2

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