# Temporal Upsampling of Depth Maps Using a Hybrid Camera

arXiv: https://arxiv.org/abs/1708.03760 · HTML: https://mlsanity.com/paper/1708.03760/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2017.

## Built on by (most cited first, 4 of 4)

- [Lifting Monocular Events to 3D Human Poses](https://mlsanity.com/paper/2104.10609/) (2021)
- [AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras](https://mlsanity.com/paper/2305.14731/) (2023)
- [Refinement of Monocular Depth Maps via Multi-View Differentiable Rendering](https://mlsanity.com/paper/2410.03861/) (2024)
- [UniRED: Unified RGB-D Video Frame Interpolation with Event Guidance](https://mlsanity.com/paper/2606.24282/) (2026)

## Abstract (arXiv)

In recent years, consumer-level depth cameras have been adopted for various applications. However, they often produce depth maps at only a moderately high frame rate (approximately 30 frames per second), preventing them from being used for applications such as digitizing human performance involving fast motion. On the other hand, low-cost, high-frame-rate video cameras are available. This motivates us to develop a hybrid camera that consists of a high-frame-rate video camera and a low-frame-rate depth camera and to allow temporal interpolation of depth maps with the help of auxiliary color images. To achieve this, we develop a novel algorithm that reconstructs intermediate depth maps and estimates scene flow simultaneously. We test our algorithm on various examples involving fast, non-rigid motions of single or multiple objects. Our experiments show that our scene flow estimation method is more precise than a tracking-based method and the state-of-the-art techniques.