Single Image 3D Reconstruction

Single image 3D reconstruction aims to create a three-dimensional model of an object from a single photograph, a challenging inverse problem due to inherent ambiguity. Current research focuses on improving accuracy and efficiency, employing neural radiance fields (NeRFs), Gaussian splatting, and diffusion models, often incorporating transformers or other attention mechanisms for improved feature extraction and scene understanding. These advancements are driving progress in applications such as 3D-aware image editing, novel view synthesis, and even text-to-3D generation, impacting fields ranging from computer graphics to robotics. The development of faster, more robust, and more accurate methods remains a key area of ongoing investigation.