Two-step method for geometry reconstruction using differentiable rendering

The task of reconstructing real-world objects arises in many areas of human life. Inverse rendering methods show high efficiency in solving this problem. For accurate reconstruction of object geometry from a set of images, we propose a geometry reconstruction method based on differentiable rendering. This method consists of two steps: forming a bounding volume and optimizing the geometry. To achieve high-speed geometry reconstruction, we suggest reducing the time spent on optimizing the silhouette gradients by conducting an initial stage of constructing the bounding volume of the object. The article considers the possibility of using three-dimensional visual hulls as a primary representation for optimizing geometry using differentiable rendering methods. Introducing this stage of geometry reconstruction allows the inverse rendering to start with the condition of matching the reconstructed object's contour and topology. Thus, geometry optimization occurs considering shading gradients, eliminating the need to account for object silhouette gradients. The proposed approach solves the problem related to potential distortion of the object's geometry, such as normal inversion or self-intersecting triangles. The paper presents the results of applying the proposed method to reconstruct test objects from image sets and demonstrates the increase in accuracy of geometry reconstruction.