Simultaneous localization and mapping (SLAM) techniques are widely researched, since
they allow the simultaneous creation of a map and the sensors' pose estimation in an …

Autonomous driving vehicles require both a precise localization and mapping solution in
different driving environment. In this context, Simultaneous Localization and Mapping …

We present a new test-time optimization method for estimating dense and long-range motion
from a video sequence. Prior optical flow or particle video tracking algorithms typically …

Understanding and reasoning about spatial relationships is crucial for Visual Question
Answering (VQA) and robotics. Vision Language Models (VLMs) have shown impressive …

Over the last decade, neural networks have reached almost every field of science and
become a crucial part of various real world applications. Due to the increasing spread …

In this paper we introduce GS-SLAM that first utilizes 3D Gaussian representation in the
Simultaneous Localization and Mapping (SLAM) system. It facilitates a better balance …

Active simultaneous localization and mapping (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …

Augmented Reality (AR) is an augmented depiction of reality formed by overlaying digital
information on an image of objects being seen through a device. Artificial Intelligence (AI) …

Unknown correlations (UCs) generally exist in a wide spectrum of practical multi-source
information fusion problems, and thereby, their corresponding fusion problems have …

Autonomous underwater vehicles (AUVs) are submersible underwater vehicles controlled
by onboard computers. AUV formation is a cooperative control which focuses on controlling …