Room Layout Estimation

Room layout estimation aims to automatically reconstruct the 3D structure of a room from visual input, typically a single panoramic image or a set of images. Current research focuses on improving accuracy and robustness, particularly in handling occlusions and ambiguous regions, using various approaches including transformer networks, geometry-aware ray casting, and multi-view consistency checks. These advancements leverage both 2D and 3D information, often incorporating self-supervised learning techniques to address data limitations. The resulting accurate and efficient room layout estimations have significant implications for applications such as virtual/augmented reality, robotics, and 3D modeling.