UW Indoor Scenes (UW-IS) Dataset

UW Indoor Scenes (UW-IS) dataset is an RGB dataset for evaluating object recognition performance in multiple, typical indoor environments. The UW-IS dataset consists of indoor scenes taken in two completely different environments. The first environment is a living room scene where objects are placed on a tabletop. The second environment is a mock warehouse setup where objects are placed on a shelf. We select a fixed set of fourteen different objects from the benchmark Yale-CMU-Berkeley (YCB) object and model set for our dataset. For the living room environment, we have a total of 347 scene images. The images are taken in four different illumination settings from three different camera perspectives and varying distances up to two meters. Sixteen out of the 347 scene images are with two different objects, 135 images are with three different objects, 156 images are with four different objects, and 40 images are with five different objects. For the mock warehouse environment, we have a total of 200 scene images taken from distances up to 1.6 meters. Sixty out of 200 images are images with three different objects, 68 images with four different objects, and 72 images are with five different objects.