This paper tackles the problem of depth estimation from a single image. Existing work either
focuses on generalization performance disregarding metric scale, ie relative depth …

Camera pose estimation is a long-standing computer vision problem that to date often relies
on classical methods, such as handcrafted keypoint matching, RANSAC and bundle …

The integration of neural rendering and the SLAM system recently showed promising results
in joint localization and photorealistic view reconstruction. However existing methods fully …

Abstract We propose Deep Patch Visual Odometry (DPVO), a new deep learning system for
monocular Visual Odometry (VO). DPVO uses a novel recurrent network architecture …

Perception plays a crucial role in various robot applications. However existing well-
annotated datasets are biased towards autonomous driving scenarios while unlabelled …

This paper discusses the results for the second edition of the Monocular Depth Estimation
Challenge (MDEC). This edition was open to methods using any form of supervision …

The advancement of autonomous drones essential for sectors such as remote sensing and
emergency services is hindered by the absence of training datasets that fully capture the …

Stereo matching methods based on iterative optimization like RAFT-Stereo and IGEV-Stereo
have evolved into a cornerstone in the field of stereo matching. However these methods …

Accurate intrinsic calibration is essential for camera-based 3D perception, yet, it typically
requires targets of well-known geometry. Here, we propose a camera self-calibration …

Implicit neural SLAM has achieved remarkable progress recently. Nevertheless existing
methods face significant challenges in non-ideal scenarios such as motion blur or lighting …