ToF 360 Dataset Overview The ToF 360 dataset consists of spherical RGB D images with instance level semantic and room layout annotations, which include 4 unique scenes. It contains 179 equirectangular RGB images along with the corresponding depths, surface normals, XYZ images, and HHA images, labeled with building defining object categories and image based layout boundaries (ceiling wall, wall floor). The dataset enables development of scene understanding tasks based on single shot reconstruction without the need for global alignment in indoor spaces. You can also find the paper here. Dataset Modalities Each scenes in the dataset has its own folder in the dataset. All the modalities for each area are contained in that folder as / . RGB images: RGB images contain equirectangular 24 bit color and it is converted from raw dual fisheye image taken by a sensor. Manhattan aligned RGB images: We followed the preprocessing code proposed by [[LGT Net]](https://github.com/zhigangjiang/LGT Net) to create Manhattan aligned RGB images. Sample code for our dataset is in assets/preprocessing/align manhattan.py . depth: Depth images are stored as 16 bit grayscale PNGs having a maximum depth of 128…
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