INS Dataset

A significant challenge in removing shadows from indoor scenes is obtaining shadow-free images. To overcome this challenge, we propose a novel rendering pipeline for generating shadowed and shadow-free images under direct and indirect illumination, and create a comprehensive synthetic dataset that contains over 30,000 image pairs, covering various object types and lighting conditions.

We implemented a direct/indirect shadow and shadow-free rendering pipeline using Blender Cycles engine, with the help of Open Shading Language (OSL). The resulting collection of shadow and shadow-free images is referred to as the “INS dataset”. The dataset includes 30,000 training and 2,000 testing images, all with a resolution of 512 × 512. The training and testing images are generated from distinct scenes with different objects and materials.