🗃️ PanoInfinigen Dataset PanoInfinigen is a synthetic dataset of high resolution panoramic images in ERP, featuring perfectly aligned RGB, Depth, and Surface Normals. This dataset was generated using a modified Infinigen framework to support wide angle panoramic geometry, plus the iCity procedural city generator for the urban split. It serves as the primary training data for PaGeR, a single step diffusion model for zero shot panoramic depth and normal estimation. Dataset Summary Content: Synthetic indoor, nature, and urban scenes. Modality: RGB (PNG), Depth (binary .npy), Surface Normals (binary .npy). Projection: Equirectangular (ERP). Use Case: Training and evaluating monocular panoramic depth and normal estimation models. Data Structure The dataset is split into three configurations: indoor , nature , and urban . Each contains train , validation , and test splits. Feature Type Description : : : image PIL.Image 8 bit RGB Panoramic Image. depth binary float16 NumPy array. Range: [0, 75] m for indoor / nature , [0, 500] m for urban . normals binary float16 NumPy array. Range: [ 1, 1]. How to Use Since depth and normals are stored as binary blobs to preserve precision (float16), yo…
Runs entirely in your browser via DuckDB-Wasm — this dataset's real data file is loaded once, then queried locally. Nothing is sent to a server.
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