Estimating the relative depth of a scene is a significant step towards understanding the general structure of the depicted scenery, the relations of entities in the scene and their interactions. When faced with the task of estimating depth without the use of Stereo images, we are dependent on the availability of large-scale depth datasets and high-capacity models to capture the intrinsic nature of depth. Unfortunately, creating datasets of depth images is not a trivial task as the requirements for the camera mainly limits us to areas where we can provide the necessities for the camera to work. In this work, we present a new depth dataset captured from Video Games in an easy and reproducible way. The nature of open-world video games gives us the ability to capture high-quality depth maps in the wild without the constrictions of Stereo cameras. Experiments on this dataset shows that using such synthetic datasets increases the accuracy of Monocular Depth Estimation in the wild where other approaches usually fail to generalize.
By considering a scene as a combination of Foreground and Background and having the aid of users to determine these two layers, one can estimate the global depth of a scene @cite_17 . The main problem of these approaches is the need of user hints about the relative depth of the scene without which the estimation would not be able to work.
@cite_17
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In this paper, we propose an interactive technique for constructing a 3D scene via sparse user inputs. We represent a 3D scene in the form of a Layered Depth Image LDI which is composed of a foreground layer and a background layer, and each layer has a corresponding texture and depth map. Given user-specified sparse depth inputs, depth maps are computed based on superpixels using interpolation with geodesic-distance weighting and an optimization framework. This computation is done immediately, which allows the user to edit the LDI interactively. Additionally, our technique automatically estimates depth and texture in occluded regions using the depth discontinuity. In our interface, the user paints strokes on the 3D model directly. The drawn strokes serve as 3D handles with which the user can pull out or push the 3D surface easily and intuitively with real-time feedback. We show our technique enables efficient modeling of LDI that produce sufficient 3D effects.