1. 03 Nov, 2020 1 commit
    • Christoph Lassner's avatar
      pulsar integration. · b19fe1de
      Christoph Lassner authored
      Summary:
      This diff integrates the pulsar renderer source code into PyTorch3D as an alternative backend for the PyTorch3D point renderer. This diff is the first of a series of three diffs to complete that migration and focuses on the packaging and integration of the source code.
      
      For more information about the pulsar backend, see the release notes and the paper (https://arxiv.org/abs/2004.07484). For information on how to use the backend, see the point cloud rendering notebook and the examples in the folder `docs/examples`.
      
      Tasks addressed in the following diffs:
      * Add the PyTorch3D interface,
      * Add notebook examples and documentation (or adapt the existing ones to feature both interfaces).
      
      Reviewed By: nikhilaravi
      
      Differential Revision: D23947736
      
      fbshipit-source-id: a5e77b53e6750334db22aefa89b4c079cda1b443
      b19fe1de
  2. 21 Aug, 2020 1 commit
    • Georgia Gkioxari's avatar
      camera refactoring · 57a22e73
      Georgia Gkioxari authored
      Summary:
      Refactor cameras
      * CamerasBase was enhanced with `transform_points_screen` that transforms projected points from NDC to screen space
      * OpenGLPerspective, OpenGLOrthographic -> FoVPerspective, FoVOrthographic
      * SfMPerspective, SfMOrthographic -> Perspective, Orthographic
      * PerspectiveCamera can optionally be constructred with screen space parameters
      * Note on Cameras and coordinate systems was added
      
      Reviewed By: nikhilaravi
      
      Differential Revision: D23168525
      
      fbshipit-source-id: dd138e2b2cc7e0e0d9f34c45b8251c01266a2063
      57a22e73
  3. 16 Jul, 2020 1 commit
    • Nikhila Ravi's avatar
      barycentric clipping in cuda/c++ · cc70950f
      Nikhila Ravi authored
      Summary:
      Added support for barycentric clipping in the C++/CUDA rasterization kernels which can be switched on/off via a rasterization setting.
      
      Added tests and a benchmark to compare with the current implementation in PyTorch - for some cases of large image size/faces per pixel the cuda version is 10x faster.
      
      Reviewed By: gkioxari
      
      Differential Revision: D21705503
      
      fbshipit-source-id: e835c0f927f1e5088ca89020aef5ff27ac3a8769
      cc70950f