Lecturers, as the guidance of the classroom, play a significant role in the teaching process.
However, the lecturers' sense of space immersion has been ignored in current virtual …

Learning-based stereo methods usually require a large scale dataset with depth, however
obtaining accurate depth in the real domain is difficult, but groundtruth depth is readily …

Structured light-based depth sensors provide accurate depth information independently of
the scene appearance by extracting pattern positions from the captured pixel intensities …

Depth from structured light (SL) is a mainstream approach for 3D acquisition. In this article,
we propose a unique depth reconstruction method for single-shot SL systems, which …

We introduce a novel depth estimation technique for multi-frame structured light setups
using neural implicit representations of 3D space. Our approach employs a neural signed …

In recent years, deep neural networks have shown remarkable progress in dense disparity
estimation from dynamic scenes in monocular structured light systems. However, their …

The structured light (SL)-based 3D measurement techniques with deep learning have been
widely studied, among which speckle projection profilometry (SPP) and fringe projection …

We introduced Temporally Incremental Disparity Estimation Network (TIDE-Net), a learning-
based technique for disparity computation in mono-camera structured light systems. In our …

This paper introduces a novel neuro-geometric methodology for single image object depth
estimation, abbreviated as NGDE. The proposed methodology can be described as a hybrid …

This paper introduces a novel neuro-geometric methodology for single image object depth
estimation, abbreviated as NGDE. The proposed methodology can be described as a hybrid …