LightS: Light Specularity Dataset
LightS: Light Specularity Dataset
Datasets
LightS: Light Specularity Dataset
File
LightS: Light Specularity Dataset
Use Case
Computer Vision
Description
Discover the LightS Specularity Dataset, featuring 2603 photo-realistic rendered views from professionally designed indoor scenes.
Overview:
The LightS dataset features a collection of indoor, photo-realistic images derived from Physically Based Rendering (PBR) of various scenes. Designed primarily to facilitate research on how light interacts with objects, particularly focusing on specular highlights, this dataset is versatile enough for broader applications. These include, but are not limited to, shadow detection, normal estimation, and depth estimation.
Composition and Features:
Spanning 18 different indoor environments such as bedrooms, bathrooms, and living rooms, LightS is built on meticulously designed CAD models by professional architects. These models emphasize optimal light scattering effects within each scene. The dataset uniquely manipulates light intensities across three levels (high, normal, and low) to enhance the occurrence and observation of specularity — both direct and indirect. Direct specularity arises when light reflects off surfaces directly from a light source, while indirect specularity occurs through light reflected off other surfaces, such as mirrors.
Technical Details:
LightS comprises 2,603 high-quality rendered views, each at a resolution of 1280×1024. These renders are generated using Blender’s Cycles rendering engine, employing path tracing as the light transport model. Each scene’s lighting parameters have been finely tuned to showcase varied light interactions. LightS stands out by offering richer material properties compared to SunCG, greater camera angle variation than MatterPort3D, and significantly more images than other directly comparable datasets.
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