User-Driven Customization in 3D Generation: Improving Stable Fast 3D with Inpainting Methods

Stable Fast 3D is widely recognized for its remarkable capacity to generate 3D models from a single 2D image in as little as 0.5 seconds. This can be further improved upon by utilizing text-to-image latent diffusion especially using the inpainting technique in the stable diffusion. The purpose of this work is to improve the quality and fidelity of the generation of 3D models by allowing user-guided customizations during the reconstruction process. Inpainting confronts two significant challenges: incomplete or noisy input data, and visualization differences, by completing unobserved areas and improving input textures. Inpainting enables users to iteratively modify their inputs, and potentially provide more coherent and aesthetically pleasing final 3D models. Experimental results indicate that by utilizing inpainting incoporated with Stable Fast 3D, increases the model precision, while retaining the original speed of model generation. The method proposed in this paper expands the use of 3D reconstruction techniques to other domains including gaming, virtual reality, and product design by providing a solution that is both more interactive and easier to create high-quality 3D assets.