Multi-view stereo infers the 3D geometry from a set of images captured from several known
positions and viewpoints. It is one of the most important components of 3D reconstruction …

We present PanopticNeRF, an object-aware neural scene representation that decomposes
a scene into a set of objects (things) and background (stuff). Each object is represented by a …

Abstract 3D scene understanding plays a vital role in vision-based autonomous driving.
While most existing methods focus on 3D object detection, they have difficulty describing …

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

We present cross-view transformers, an efficient attention-based model for map-view
semantic segmentation from multiple cameras. Our architecture implicitly learns a mapping …

In this work, we present a new multi-view depth estimation method that utilizes both
conventional SfM reconstruction and learning-based priors over the recently proposed …

This paper addresses the challenge of reconstructing 3D indoor scenes from multi-view
images. Many previous works have shown impressive reconstruction results on textured …

Very recently neural implicit rendering techniques have been rapidly evolved and shown
great advantages in novel view synthesis and 3D scene reconstruction. However, existing …

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

In this paper, we propose M $^ 2$ BEV, a unified framework that jointly performs 3D object
detection and map segmentation in the Birds Eye View~(BEV) space with multi-camera …