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Infografía que resume los aspectos más destacables de la asignatura Dirección Estratégica de las Tecnologías de la Información del Master Universitario en Ingeniería Informática de la Universidad de Alicante. Redactados en forma de mantras, son los principios que deben repetirse los estudiantes a lo largo del curso para interiorizarlos y que leemos todos los días antes de empezar las clases de la asignatura. Infographic that summarizes the most outstanding aspects of the subject Strategic Information Technologies Management of the University Master’s degree in Computer Engineering at the University of Alicante. Written in the form of mantras, these are the principles that students must repeat throughout the course to internalize them and that we read every day before starting lessons in the subject.

Enter the RobotriX, an extremely photorealistic indoor dataset designed to enable the application of deep learning techniques to a wide variety of robotic vision problems. The RobotriX consists of hyperrealistic indoor scenes which are explored by robot agents which also interact with objects in a visually realistic manner in that simulated world. Photorealistic scenes and robots are rendered by Unreal Engine into a virtual reality headset which captures gaze so that a human operator can move the robot and use controllers for the robotic hands; scene information is dumped on a per-frame basis so that it can be reproduced offline using UnrealCV to generate raw data and ground truth labels. By taking this approach we were able to generate a dataset of 38 semantic classes across 512 sequences totaling 8M stills recorded at +60 frames per second with full HD resolution. For each frame, RGB-D and 3D information is provided with full annotations in both spaces. Thanks to the high quality and quantity of both raw information and annotations, the RobotriX will serve as a new milestone for investigating 2D and 3D robotic vision tasks with large-scale data-driven techniques. Instituto Universitario de Investigación en Informática (Grupo de Interés 3D Perception Lab). This work has been also funded by the Spanish Government TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds. This work has also been supported by a Spanish national grant for PhD studies FPU15/04516 and by the University of Alicante project GRE16-19 and by the Valencian Government project GV/2018/022. Experiments were made possible by a generous hardware donation from NVIDIA.