# Exploring Stereovision-Based 3-D Scene Reconstruction for Augmented Reality

arXiv: https://arxiv.org/abs/1902.06255 · HTML: https://mlsanity.com/paper/1902.06255/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 17 Feb 2019.

## Built on by (most cited first, 1 of 1)

- [MLG-Stereo: ViT Based Stereo Matching with Multi-Stage Local-Global Enhancement](https://mlsanity.com/paper/2604.20393/) (2026)

## Abstract (arXiv)

Three-dimensional (3-D) scene reconstruction is one of the key techniques in Augmented Reality (AR), which is related to the integration of image processing and display systems of complex information. Stereo matching is a computer vision based approach for 3-D scene reconstruction. In this paper, we explore an improved stereo matching network, SLED-Net, in which a Single Long Encoder-Decoder is proposed to replace the stacked hourglass network in PSM-Net for better contextual information learning. We compare SLED-Net to state-of-the-art methods recently published, and demonstrate its superior performance on Scene Flow and KITTI2015 test sets.