# LookUp3D: Data-Driven 3D Scanning

arXiv: https://arxiv.org/abs/2405.14882 · HTML: https://mlsanity.com/paper/2405.14882/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 50 references that are in the map.
- First posted on arXiv 5 Apr 2024.

## Builds on (most cited first, 3 of 3)

- [Deep Polarization Imaging for 3D shape and SVBRDF Acquisition](https://mlsanity.com/paper/2105.02875/) (2021)
- [ESL: Event-based Structured Light](https://mlsanity.com/paper/2111.15510/) (2021)
- [An Overview of Depth Cameras and Range Scanners Based on Time-of-Flight Technologies](https://mlsanity.com/paper/2012.06772/) (2020)

## Abstract (arXiv)

High speed, high-resolution, and accurate 3D scanning would open doors to many new applications in graphics, robotics, science, and medicine by enabling the accurate scanning of deformable objects during interactions. Past attempts to use structured light, time-of-flight, and stereo in high-speed settings have usually required tradeoffs in resolution or inaccuracy. In this paper, we introduce a method that enables, for the first time, 3D scanning at 450 frames per second at 1~Megapixel, or 1,450 frames per second at 0.4~Megapixel in an environment with controlled lighting. The key idea is to use a per-pixel lookup table that maps colors to depths, which is built using a linear stage. Imperfections, such as lens-distortion and sensor defects are baked into the calibration. We describe our method and test it on a novel hardware prototype. We compare the system with both ground-truth geometry as well as commercially available dynamic sensors like the Microsoft Kinect and Intel Realsense. Our results show the system acquiring geometry of objects undergoing high-speed deformations and oscillations and demonstrate the ability to recover physical properties from the reconstructions.