The ability to predict, anticipate and reason about future outcomes is a key component of
intelligent decision-making systems. In light of the success of deep learning in computer …

Reconstructing accurate 3D scenes from images is a long-standing vision task. Due to the ill-
posedness of the single-image reconstruction problem, most well-established methods are …

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 …

Data-driven algorithms have surpassed traditional techniques in almost every aspect in
robotic vision problems. Such algorithms need vast amounts of quality data to be able to …

The underground coal mine production of the fully mechanized mining face exists many
problems, such as poor operating environment, high accident rate and so on. Recently, the …

In this study, we address the challenge of 3D scene structure recovery from monocular depth
estimation. While traditional depth estimation methods leverage labeled datasets to directly …

In many applications, such as robotic perception, scene understanding, augmented reality,
3D reconstruction, and medical image analysis, depth from images is a fundamentally ill …

The ongoing biodiversity crisis calls for accurate estimation of animal density and
abundance to identify sources of biodiversity decline and effectiveness of conservation …

Building upon the recent progress in novel view synthesis, we propose its application to
improve monocular depth estimation. In particular, we propose a novel training method split …

Monocular depth estimation methods have achieved excellent robustness on diverse
scenes, usually by predicting affine-invariant depth, up to an unknown scale and shift, rather …