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Depth Map Super-Resolution

Depth map super-resolution is the task of upsampling depth images.

( Image credit: A Joint Intensity and Depth Co-Sparse Analysis Model for Depth Map Super-Resolution )

Papers

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Showing 1–10 of 28 papers

TitleStatusHype
Learning Continuous Depth Representation via Geometric Spatial AggregatorCode1
Discrete Cosine Transform Network for Guided Depth Map Super-ResolutionCode1
Guided Depth Map Super-resolution: A SurveyCode1
High-resolution Depth Maps Imaging via Attention-based Hierarchical Multi-modal FusionCode1
SGNet: Structure Guided Network via Gradient-Frequency Awareness for Depth Map Super-ResolutionCode1
Deep Attentional Guided Image FilteringCode1
Deformable Kernel Networks for Joint Image FilteringCode1
CoReGAN: Contrastive Regularized Generative Adversarial Network for Guided Depth Map Super Resolution—0
Content-aware Directed Propagation Network with Pixel Adaptive Kernel Attention—0
BridgeNet: A Joint Learning Network of Depth Map Super-Resolution and Monocular Depth Estimation—0
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