3D AI Tools
Free 3D AI tools for creating, optimizing, and manipulating 3D assets for games, films, and design projects, boosting your creative process.
[MCC-Hand-Object (MCC-HO)] can reconstruct 3D shapes of hand-held objects from a single RGB image and a 3D hand model. It uses Retrieval-Augmented Reconstruction (RAR) with GPT-4(V) to match 3D models to the object’s shape, achieving top performance on various datasets.
SpatialTracker can track 2D pixels in 3D space, even when objects are blocked or rotated. It uses depth estimators and a triplane representation to achieve top performance in difficult situations.
InstructHumans can edit existing 3D human textures using text prompts. It maintains avatar consistency pretty well and enables easy animation.
ProbTalk is a method for generating lifelike holistic co-speech motions for 3D avatars. The method is able to generate a wide range of motions and ensures a harmonious alignment among facial expressions, hand gestures, and body poses.
GaussianCube is a image-to-3D model that is able to generate high-quality 3D objects from multi-view images. This one also uses 3D Gaussian Splatting, converts the unstructured representation into a structured voxel grid, and then trains a 3D diffusion model to generate new objects.
Garment3DGen can stylize the geometry and textures from 2D image and 3D mesh garments! These can be fitted on top of parametric bodies and simulated. Could be used for hand-garment interaction in VR or to turn sketches into 3D garments.
MonoHair can create high-quality 3D hair from a single video. It uses a two-step process for detailed hair reconstruction and achieves top performance across various hairstyles.
AiOS can estimate human poses and shapes in one step, combining body, hand, and facial expression recovery.
TC4D can animate 3D scenes generated from text along arbitrary trajectories. I can see this being useful for generating 3D effects for movies or games.
Make-It-Vivid generates high-quality texture maps for 3D biped cartoon characters from text instructions, making it possible to dress and animate characters based on prompts.
ThemeStation can generate a variety of 3D assets that match a specific theme from just a few examples. It uses a two-stage process to improve the quality and diversity of the models, allowing users to create 3D assets based on their own text prompts.
TexDreamer can generate high-quality 3D human textures from text and images. It uses a smart fine-tuning method and a unique translator module to create realistic textures quickly while keeping important details intact.
HoloDreamer can generate enclosed 3D scenes from text descriptions. It does so by first creating a high-quality equirectangular panorama and then rapidly reconstructing the 3D scene using 3D Gaussian Splatting.
InTeX can enable interactive text-to-texture synthesis for 3D content creation. It allows users to repaint specific areas and edit textures precisely, while a depth-aware inpainting model reduces 3D inconsistencies and speeds up generation.
Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting can create high-quality 3D content from text prompts. It uses edge, depth, normal, and scribble maps in a multi-view diffusion model, enhancing 3D shapes with a unique hybrid guidance method.
StyleGaussian on the other hand enables instant style transfer of any image’s style to a 3D scene at 10fps while preserving strict multi-view consistency.
SplattingAvatar can generate photorealistic real-time human avatars using a mix of Gaussian Splatting and triangle mesh geometry. It achieves over 300 FPS on modern GPUs and 30 FPS on mobile devices, allowing for detailed appearance modeling and various animation techniques.
TripoSR can generate high-quality 3D meshes from a single image in under 0.5 seconds.
ViewDiff is a method that can generate high-quality, multi-view consistent images of a real-world 3D object in authentic surroundings from a single text prompt or a single posed image.
GEM3D is a deep, topology-aware generative model of 3D shapes. The method is able to generate diverse and plausible 3D shapes from user-modeled skeletons, making it possible to draw the rough structure of an object and have the model fill in the rest.