We read and discuss
Image-based rendering in the gradient domain by Johannes Kopf, Fabian Langguth, Daniel Scharstein, Rick Szeliski, Michael Goesele. ACM Transactions on Graphics (Proc. SIGGRAPH Asia 2013) | December 2013 pdf

Project website: https://johanneskopf.de/publications/gdibr/

Video: https://johanneskopf.de/publications/gdibr/video/gdibr.mp4

Papers we considered

  1. Image-based rendering in the gradient domain https://johanneskopf.de/publications/gdibr/ - SELECTED
  2. Unsupervised Monocular Training Method for Depth Estimation Using Statistical Masks: pdf
  3. Forget About the LiDAR
  4. Footprints and free space from a single color image
  5. Unsupervised Moving Object Detection via Contextual Information Separation
  6. Unsupervised Monocular Depth Learning in Dynamic Scenes

  7. MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask pdf

    It is one of the fastest among the top methods at cvlibs benchmark + open source.