Temporal Upsampling of Depth Maps Using a Hybrid Camera
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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.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 Aug 2017.
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Citing papers per year: 2021: 1; 2022: 0; 2023: 1; 2024: 1; 2025: 0; 2026: 1.
4 papers.
- 2021Lifting Monocular Events to 3D Human Posescited by 16
- 2023AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Camerascited by 1
- 2024Refinement of Monocular Depth Maps via Multi-View Differentiable Renderingcited by 1
- 2026UniRED: Unified RGB-D Video Frame Interpolation with Event Guidancecited by 0
- 2026UniRED: Unified RGB-D Video Frame Interpolation with Event Guidance23 Jun 2026
- 2024Refinement of Monocular Depth Maps via Multi-View Differentiable Rendering4 Oct 2024
- 2023AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras24 May 2023
- 2021Lifting Monocular Events to 3D Human Poses21 Apr 2021