Automated guided vehicles (AGVs) and autonomous mobile robots (AMRs) have been
widely used recently to solve various engineering problems in logistics, manufacturing, and …

Simultaneous Localization and Mapping is now widely adopted by many applications, and
researchers have produced very dense literature on this topic. With the advent of smart …

Neural implicit representations have recently shown encouraging results in various
domains, including promising progress in simultaneous localization and mapping (SLAM) …

We propose a novel geometric and photometric 3D mapping pipeline for accurate and real-
time scene reconstruction from casually taken monocular images. To achieve this, we …

We show for the first time that a multilayer perceptron (MLP) can serve as the only scene
representation in a real-time SLAM system for a handheld RGB-D camera. Our network is …

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 …

We present ESLAM, an efficient implicit neural representation method for Simultaneous
Localization and Mapping (SLAM). ESLAM reads RGB-D frames with unknown camera …

Neural implicit representations have recently become popular in simultaneous localization
and mapping (SLAM), especially in dense visual SLAM. However, existing works either rely …

We propose a dense neural simultaneous localization and mapping (SLAM) approach for
monocular RGBD input which anchors the features of a neural scene representation in a …

Traditionally, 3D indoor scene reconstruction from posed images happens in two phases:
per-image depth estimation, followed by depth merging and surface reconstruction …