Noname manuscript No. (will be inserted by the editor) Demisting the Hough Transform for 3D Shape Recognition and Registration

Citations in the corpus

• ImVoteNet: Boosting 3D Object Detection in Point Clouds With Image Votes (2020, methodology): “Most relevant to our work are PointRCNN [41] and Deep Hough Voting (VOTENET) [33] (related to earlier Hough voting ideas [47, 50, 16, 15]) which demonstrated state-ofthe-art 3D object detection in outdoor and indoor scenes, respectively.”
• Go-ICP: A Globally Optimal Solution to 3D ICP Point-Set Registration (2016, background): “Equations (1) and (2) actually form a well-known chicken-and-egg problem: if the true correspondences are known a priori , the transformation can be optimally solved in closed-form [56], [57]; if the optimal transformation is given, correspondences can also be readily found.”
• Sliding Shapes for 3D Object Detection in Depth Images (2014, background): “Voting: There are many works focus on how to integrate local information via voting [20, 45–49], such as Hough voting or Implicit Shape Model.”