Symmetric Uncertainty-Aware Feature Transmission for Depth Super-Resolution

by   Wuxuan Shi, et al.
Wuhan University

Color-guided depth super-resolution (DSR) is an encouraging paradigm that enhances a low-resolution (LR) depth map guided by an extra high-resolution (HR) RGB image from the same scene. Existing methods usually use interpolation to upscale the depth maps before feeding them into the network and transfer the high-frequency information extracted from HR RGB images to guide the reconstruction of depth maps. However, the extracted high-frequency information usually contains textures that are not present in depth maps in the existence of the cross-modality gap, and the noises would be further aggravated by interpolation due to the resolution gap between the RGB and depth images. To tackle these challenges, we propose a novel Symmetric Uncertainty-aware Feature Transmission (SUFT) for color-guided DSR. (1) For the resolution gap, SUFT builds an iterative up-and-down sampling pipeline, which makes depth features and RGB features spatially consistent while suppressing noise amplification and blurring by replacing common interpolated pre-upsampling. (2) For the cross-modality gap, we propose a novel Symmetric Uncertainty scheme to remove parts of RGB information harmful to the recovery of HR depth maps. Extensive experiments on benchmark datasets and challenging real-world settings suggest that our method achieves superior performance compared to state-of-the-art methods. Our code and models are available at


page 1

page 3

page 4

page 5

page 6

page 7

page 8


Depth Super-Resolution from Explicit and Implicit High-Frequency Features

We propose a novel multi-stage depth super-resolution network, which pro...

Joint Implicit Image Function for Guided Depth Super-Resolution

Guided depth super-resolution is a practical task where a low-resolution...

Learning Scene Structure Guidance via Cross-Task Knowledge Transfer for Single Depth Super-Resolution

Existing color-guided depth super-resolution (DSR) approaches require pa...

Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution

Guided depth map super-resolution (GDSR), as a hot topic in multi-modal ...

Implicit Neural Image Stitching With Enhanced and Blended Feature Reconstruction

Existing frameworks for image stitching often provide visually reasonabl...

Light Field Reconstruction via Attention-Guided Deep Fusion of Hybrid Lenses

This paper explores the problem of reconstructing high-resolution light ...

Fast Road Segmentation via Uncertainty-aware Symmetric Network

The high performance of RGB-D based road segmentation methods contrasts ...

Please sign up or login with your details

Forgot password? Click here to reset