C2PD: Continuity-Constrained Pixelwise Deformation for Guided Depth Super-Resolution
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Abstract (arXiv)
Guided depth super-resolution (GDSR) has demonstrated impressive performance across a wide range of domains, with numerous methods being proposed. However, existing methods often treat depth maps as images, where shading values are computed discretely, making them struggle to effectively restore the continuity inherent in the depth map. In this paper, we propose a novel approach that maximizes the utilization of spatial characteristics in depth, coupled with human abstract perception of real-world substance, by transforming the GDSR issue into deformation of a roughcast with ideal plasticity, which can be deformed by force like a continuous object. Specifically, we firstly designed a cross-modal operation, Continuity-constrained Asymmetrical Pixelwise Operation (CAPO), which can mimic the process of deforming an isovolumetrically flexible object through external forces. Utilizing CAPO as the fundamental component, we develop the Pixelwise Cross Gradient Deformation (PCGD), which is capable of emulating operations on ideal plastic objects (without volume constraint). Notably, our approach demonstrates state-of-the-art performance across four widely adopted benchmarks for GDSR, with significant advantages in large-scale tasks and generalizability.
Key facts. Cited by 8 papers in the map (data through 14 Oct 2026). Builds on 28 of its 49 references that are in the map. First posted on arXiv 13 Jan 2025.
Builds on
28 of 49 references.
References · 28
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16 more
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Built on by
Citing papers per year: 2025: 3; 2026: 5.
8 papers.
- 2025DuCos: Duality Constrained Depth Super-Resolution via Foundation Modelcited by 11
- 2025SpatioTemporal Difference Network for Video Depth Super-Resolutioncited by 4
- 2025Multi-Order Matching Network for Alignment-Free Depth Super-Resolutioncited by 1
- 2026Robust Depth Super-Resolution via Adaptive Diffusion Samplingcited by 0
- 2026Robust Self-Supervised Cross-Modal Super-Resolution against Real-World Misaligned Observationscited by 0
- 2026DegBins: Degradation-Driven Binning for Depth Super-Resolutioncited by 0
- 2026WAVE: Reversing the Guidance Hierarchy for Coarse-to-Fine Guided Depth Super-Resolutioncited by 0
- 2026FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolutioncited by 0
- 2026FoundDSR: A Generalizable Foundation Model with Guided 2D Gaussian Splatting for Depth Super-Resolution26 Sep 2026
- 2026WAVE: Reversing the Guidance Hierarchy for Coarse-to-Fine Guided Depth Super-Resolution26 Aug 2026
- 2026DegBins: Degradation-Driven Binning for Depth Super-Resolution10 May 2026
- 2026Robust Self-Supervised Cross-Modal Super-Resolution against Real-World Misaligned Observations21 Feb 2026
- 2026Robust Depth Super-Resolution via Adaptive Diffusion Sampling10 Feb 2026
- 2025Multi-Order Matching Network for Alignment-Free Depth Super-Resolution20 Nov 2025
- 2025SpatioTemporal Difference Network for Video Depth Super-Resolution2 Aug 2025
- 2025DuCos: Duality Constrained Depth Super-Resolution via Foundation Model6 Mar 2025