2019/01/19 by A. García-García, Pablo Martínez-González, Garcia-Garcia, Alberto +11
Computer Science · Engineering · #Advanced Neural Network Applications #Advanced Vision and Imaging #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Machine Learning (cs.LG) #Robotics (cs.RO) #Robotics and Sensor-Based Localization
paper · pdf · doi:10.48550/arxiv.1901.06514
openalex publication_date 2019/01/19 · openalex created_date 2022/10/01 · openalex updated_date 2026/07/28
Enter the RobotriX, an extremely photorealistic indoor dataset designed to\nenable the application of deep learning techniques to a wide variety of robotic\nvision problems. The RobotriX consists of hyperrealistic indoor scenes which\nare explored by robot agents which also interact with objects in a visually\nrealistic manner in that simulated world. Photorealistic scenes and robots are\nrendered by Unreal Engine into a virtual reality headset which captures gaze so\nthat a human operator can move the robot and use controllers for the robotic\nhands; scene information is dumped on a per-frame basis so that it can be\nreproduced offline to generate raw data and ground truth labels. By taking this\napproach, we were able to generate a dataset of 38 semantic classes totaling 8M\nstills recorded at +60 frames per second with full HD resolution. For each\nframe, RGB-D and 3D information is provided with full annotations in both\nspaces. Thanks to the high quality and quantity of both raw information and\nannotations, the RobotriX will serve as a new milestone for investigating 2D\nand 3D robotic vision tasks with large-scale data-driven techniques.\n