Analyzing scenes thoroughly is crucial for mobile robots acting in different environments.
Semantic segmentation can enhance various subsequent tasks, such as (semantically …

Semantic scene understanding is essential for mobile agents acting in various
environments. Although semantic segmentation already provides a lot of information, details …

Scene analysis is essential for enabling autonomous systems, such as mobile robots, to
operate in real-world environments. However, obtaining a comprehensive understanding of …

Pedestrian detection is vitally important in many computer vision tasks but still suffers from
some problems, such as illumination and occlusion if only the RGB image is exploited …

Safe interaction with pedestrians is important for autonomous vehicles in urban
environments. Comprehensive understanding of pedestrian behavior is a challenge for …

We present CineMPC, an algorithm to autonomously control a UAV-borne video camera in a
nonlinear Model Predicted Control (MPC) loop. CineMPC controls both the position and …

Depth map super-resolution (DMSR) is an effective solution to improve the quality of depth
maps captured by low-cost depth sensors. Most existing methods introduce guidance from …

Real-time prediction of human location combined with the capability to perceive obstacles is
crucial for socially-aware navigation in robotics. Our work focuses on localizing humans in …

Scene depth information plays a fundamental role and can be beneficial to various computer
vision or visual robotics applications. The scene color image acquired by consumer depth …

Person attribute estimation is a task of great importance for a variety of real-world robotic
applications. While the computer vision community has made impressive progress over the …