3D Object Generation

LVSM can generate high-quality 3D views of objects and scenes from a few input images.

StdGEN can generate high-quality 3D characters from a single image in just three minutes. It breaks down characters into parts like body, clothes, and hair, using a transformer-based model for great results in 3D anime character generation.

So far it has been tough to imagine the benefits of AI agents. Most of what we’ve seen from that domain has been focused on NPC simulations or solving text-based goals. 3D-GPT is a new framework that utilizes LLMs for instruction-driven 3D modeling by breaking down 3D modeling tasks into manageable segments to procedurally generate 3D scenes. I recently started to dig into Blender and I pray this gets open sourced at one point.

LIFe-GoM can create animatable 3D human avatars from sparse multi view images in under 1 second. It renders high-quality images at 95.1 frames per second.

Dora can generated 3D assets from images which are ready for diffusion-based character control in modern 3D engines, such as Unity 3D, in real-time.

OmniPhysGS can generate realistic 3D dynamic scenes by modeling objects with Constitutive 3D Gaussians.

Hunyuan3D 2.0 can generate high-resolution textured 3D assets. It allows users to create and animate detailed 3D models efficiently, with improved geometry detail and texture quality compared to previous models.

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.