# Depth Completion with RGB Prior

arXiv: https://arxiv.org/abs/2008.07861 · HTML: https://mlsanity.com/paper/2008.07861/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 18 Aug 2020.

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

- [BIDCD -- Bosch Industrial Depth Completion Dataset](https://mlsanity.com/paper/2108.04706/) (2021)

## Abstract (arXiv)

Depth cameras are a prominent perception system for robotics, especially when operating in natural unstructured environments. Industrial applications, however, typically involve reflective objects under harsh lighting conditions, a challenging scenario for depth cameras, as it induces numerous reflections and deflections, leading to loss of robustness and deteriorated accuracy. Here, we developed a deep model to correct the depth channel in RGBD images, aiming to restore the depth information to the required accuracy. To train the model, we created a novel industrial dataset that we now present to the public. The data was collected with low-end depth cameras and the ground truth depth was generated by multi-view fusion.