# Inferring Super-Resolution Depth from a Moving Light-Source Enhanced RGB-D Sensor: A Variational Approach

arXiv: https://arxiv.org/abs/1912.06501 · HTML: https://mlsanity.com/paper/1912.06501/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 13 Dec 2019.

## Built on by (most cited first, 8 of 8)

- [FD-Vision Mamba for Endoscopic Exposure Correction](https://mlsanity.com/paper/2402.06378/) (2024)
- [Super-resolution 3D Human Shape from a Single Low-Resolution Image](https://mlsanity.com/paper/2208.10738/) (2022)
- [FastHuman: Reconstructing High-Quality Clothed Human in Minutes](https://mlsanity.com/paper/2211.14485/) (2022)
- [SupeRVol: Super-Resolution Shape and Reflectance Estimation in Inverse Volume Rendering](https://mlsanity.com/paper/2212.04968/) (2022)
- [Sparse Views, Near Light: A Practical Paradigm for Uncalibrated Point-light Photometric Stereo](https://mlsanity.com/paper/2404.00098/) (2024)
- [High-Quality RGB-D Reconstruction via Multi-View Uncalibrated Photometric Stereo and Gradient-SDF](https://mlsanity.com/paper/2210.12202/) (2022)
- [Lifting the Convex Conjugate in Lagrangian Relaxations: A Tractable Approach for Continuous Markov Random Fields](https://mlsanity.com/paper/2107.06028/) (2021)
- [Supersampling of Data from Structured-light Scanner with Deep Learning](https://mlsanity.com/paper/2311.07432/) (2023)

## Abstract (arXiv)

A novel approach towards depth map super-resolution using multi-view uncalibrated photometric stereo is presented. Practically, an LED light source is attached to a commodity RGB-D sensor and is used to capture objects from multiple viewpoints with unknown motion. This non-static camera-to-object setup is described with a nonconvex variational approach such that no calibration on lighting or camera motion is required due to the formulation of an end-to-end joint optimization problem. Solving the proposed variational model results in high resolution depth, reflectance and camera pose estimates, as we show on challenging synthetic and real-world datasets.