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With the rapid development of computer graphics and 3D computer vision, the field of reconstructing 3D geometric shapes from sketches has quickly seen an influx of innovative methodologies. However, the majority of current methods primarily rely on the associative memory of matching images to models during their training stages, failing to fully grasp the real structure of the three-dimensional objects presented in the images. These approaches often lead to significant discrepancies between the reconstructed objects and the expected models. For instance, some methods often lose important geometric details when dealing with objects that have complex topological structures, resulting in a significant reduction in the visual consistency between the reconstructed models and the original images. Moreover, existing technologies also demonstrate clear limitations in theoretically capturing the subtle symmetry and local features of three-dimensional objects. To address this issue, we propose a two-phase framework in this work to more accurately reflect the objects in the input images in the reconstructed models. Initially, we employ an encoder–decoder structure to generate an implicit signed distance field (SDF) representing the 3D shapes. Subsequently, we carry out a comprehensive optimization of the decoder from the first phase. This process includes two main steps: firstly, utilizing differentiable rendering techniques to render the mesh model derived from the distance field, ensuring its consistency with the input images; secondly, combining the symmetry of the 3D shapes with innovative regularization loss to further refine the decoder, aiming to reduce the discrepancies between the images and the 3D shapes. Compared to similar research, our method not only demonstrates superior performance in reconstructing 3D shapes from sketches but also offers new perspectives and solutions for the optimization of 3D shapes. This work signifies an important advancement in understanding and reconstructing the transition process from sketches to precise 3D models. Code: