# Visual Mesh: Real-time Object Detection Using Constant Sample Density

arXiv: https://arxiv.org/abs/1807.08405 · HTML: https://mlsanity.com/paper/1807.08405/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2018.

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

- [Exploring GPT-4 for Robotic Agent Strategy with Real-Time State Feedback and a Reactive Behaviour Framework](https://mlsanity.com/paper/2503.23601/) (2025)

## Abstract (arXiv)

This paper proposes an enhancement of convolutional neural networks for object detection in resource-constrained robotics through a geometric input transformation called Visual Mesh. It uses object geometry to create a graph in vision space, reducing computational complexity by normalizing the pixel and feature density of objects. The experiments compare the Visual Mesh with several other fast convolutional neural networks. The results demonstrate execution times sixteen times quicker than the fastest competitor tested, while achieving outstanding accuracy.