Semantic Pose Using Deep Networks Trained on Synthetic RGB-D
Semantic Pose Using Deep Networks Trained on Synthetic RGB-D
In this work we address the problem of indoor scene understanding from RGB-D images. Specifically, we propose to find instances of common furniture classes, their spatial extent, and their pose with respect to generalized class models. To accomplish this, we use a deep, wide, multi-output convolutional neural network (CNN) that …