3D Object Generation

GaussianDreamerPro can generate 3D Gaussian assets from text that can be seamlessly integrated into downstream manipulation pipelines, such as animation, composition, and simulation.

Coin3D can generate and edit 3D assets from a basic input shape. Similar to ControlNet, this enables precise part editing and responsive 3D object previewing within a few seconds.

REACTO can reconstruct articulated 3D objects by capturing the motion and shape of objects with flexible deformation from a single video.

Trellis 3D generates high-quality 3D assets in formats like Radiance Fields, 3D Gaussians, and meshes. It supports text and image conditioning, offering flexible output format selection and local 3D editing capabilities.

Dessie can estimate the 3D shape and pose of horses from single images. It also works with other large animals like zebras and cows.

L4GM is a 4D Large Reconstruction Model that can turn a single-view video into an animated 3D object.

D3GA is the first 3D controllable model for human bodies rendered with Gaussian splats in real-time. This lets us turn ourselves or others with a multi-cam setup into a Gaussian splat which can be animated, even allowing to decompose the avatar into its different cloth layers.

GarVerseLOD can generate high-quality 3D garment meshes from a single image. It handles complex cloth movements and poses well, using a large dataset of 6,000 garment models to improve accuracy.

UniHair can create 3D hair models from single-view portraits, handling both braided and un-braided styles. It uses a large dataset and advanced techniques to accurately capture complex hairstyles and generalize well to real images.

GaussianAnything can generate high-quality 3D objects from single images or text prompts. It uses a Variational Autoencoder and a cascaded latent diffusion model for effective 3D editing.

GarmentDreamer can generate wearable, simulation-ready 3D garment meshes from text prompts. The method is able to generate diverse geometric and texture details, making it possible to create a wide range of different clothing items.

SPARK can create high-quality 3D face avatars from regular videos and track expressions and poses in real time. It improves the accuracy of 3D face reconstructions for tasks like aging, face swapping, and digital makeup.

NoPoSplat can reconstruct 3D Gaussian scenes from multi-view. It achieves real-time reconstruction and high-quality images, especially when there are few input images.

GANs aren’t dead yet. SphereHead generates stable and high-quality 3D full-head human faces from all angles with significantly fewer artifacts compared to previous methods. Best one I’ve seen so far.

HeadStudio is another text-to-3D avatar model that can generate animatable head avatars. The method is able to produce high-fidelity avatars with smooth expression deformation and real-time rendering.

Animate3D can animate any static multi-view 3D model.

AvatarGO can generate 4D human-object interaction scenes from text. It uses LLM-guided contact retargeting for accurate spatial relations and ensures smooth animations with correspondence-aware motion optimization.

And because methods always come in pairs, GenN2N is another NeRF editing method. This one can edit scenes using text prompts, colorize, upscale and inpaint them.

While TripoSR can generate meshes from an image, MagicClay can edit them. It’s an artist-friendly tool that allows you to sculpt regions of a mesh with text prompts while keeping other regions untouched.

Generative Radiance Field Relighting can relight 3D scenes captured under a single light source. It allows for realistic control over light direction and improves the consistency of views, making it suitable for complex scenes with multiple objects.