Monocular depth estimation with geometry-informed depth hint

Abstract

A depth estimation model leverages a geometry-rendered depth map from a low-cost geometry model to provide depth hints. The model is trained and configured to input a time series of frames including a target frame. The time series of images are captured as monocular video data by a camera assembly. Applying the model includes: applying a feature encoder to extract visual features forming a feature map for each frame, matching features across the features maps forming a cost volume, obtaining a geometry-rendered depth map from the low-cost geometry model of the scene based on a pose of the target frame, modifying the cost volume based on the geometry-rendered depth map, and applying a depth decoder to the modified cost volume to generate the depth map for the target frame. A client device implementing the model may generate virtual content using the depth map to display the target frame of the scene augmented with the virtual content.