Shap-E

Together with image conditioning techniques as well as prompt-based editing approach, we provide users with new ways to control 3D synthesis, opening up new avenues to various creative applications. Magic3D can create high-quality 3D textured mesh models from input text prompts. It utilizes a coarse-to-fine strategy leveraging both low- and high-resolution diffusion priors for learning the 3D representation of the target content. Magic3D synthesizes 3D content with 8× higher-resolution supervision than DreamFusion while also being 2× faster. Given a coarse model generated with a base text prompt, we can modify parts of the text in the prompt, and then fine-tune the NeRF and 3D mesh models to obtain an edited high-resolution 3D mesh.

V2Fun is an all-in-one, browser-based AI 3D creation platform that turns text prompts, reference images, and ordinary videos into production-ready 3D models and animations. Users can generate structurally accurate, perspective-correct concept images, create high-fidelity assets from text or single- and multi-view images, and use built-in prompt optimization to enrich inputs with spatial perspective, PBR materials, and fine texture parameters. Its image-to-3D and text-to-3D engines preserve artistic style, character traits, structural detail, and natural lighting while supporting rapid iteration for characters, scenes, game assets, industrial models, and 3D-printable objects. Smart retopology automatically produces clean, lightweight, editable quad meshes without sacrificing surface detail, while the AI texture generator creates or swaps complete PBR material sets with accurate lighting, bump, gloss, and roughness information.