Monocular Image Depth Restoration Method, Device, and Computer Equipment

Abstract

The invention discloses a monocular image depth restoration method and device, computer equipment, computer readable storage medium, and computer program. The method includes: performing feature extraction on the monocular image to obtain the monocular image. Feature image; decoupling the feature image to obtain a scene structure diagram of the feature image; performing gradient perception processing on the feature image and the scene structure map to obtain a region-enhanced feature image; according to the region enhancement Depth estimation is performed on the feature image of the monocular image to obtain the depth image of the monocular image.

Description

technical field [0001] The present invention relates to the field of computer vision, in particular to a monocular image depth restoration method and device, computer equipment, computer readable storage medium, and computer program. Background technique [0002] The depth restoration of monocular images refers to the depth restoration of monocular images. The depth restoration of monocular images is an important issue in the field of computer vision, and has important applications in many fields, such as 3D reconstruction, real-time positioning of robots, visual Obstacle avoidance and other fields. [0003] However, depth restoration from monocular images is a complex multi-solution problem due to the uncertainty of the depth scale. Many existing depth estimation schemes often simply couple scene structure estimation and depth scale estimation together to solve the problem at the same time, which makes the problem solving process relatively difficult, often requires more d...

AI Technical Summary

Problems solved by technology

[0003] However, depth restoration from monocular images is a complex multi-solution problem due to the uncertainty of the depth scale.

Many existing depth estimation schemes often simply couple scene structure estimation and depth scale estimation together to solve the problem at the same time, which makes the problem solving process relatively difficult, often requires more data and training time, and has low accuracy.

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