Text to 3D
55 papers with code • 1 benchmarks • 1 datasets
Benchmarks
These leaderboards are used to track progress in Text to 3D
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Libraries
Use these libraries to find Text to 3D models and implementations
T$^3$Bench
Most implemented papers
Magic3D: High-Resolution Text-to-3D Content Creation
chinhsuanwu/dreamfusionacc
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CVPR 2023
DreamFusion has recently demonstrated the utility of a pre-trained text-to-image diffusion model to optimize Neural Radiance Fields (NeRF), achieving remarkable text-to-3D synthesis results.
NeuralLift-360: Lifting An In-the-wild 2D Photo to A 3D Object with 360° Views
In this work, we study the challenging task of lifting a single image to a 3D object and, for the first time, demonstrate the ability to generate a plausible 3D object with 360{\deg} views that correspond well with the given reference image.
Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generation
We propose to apply chain rule on the learned gradients, and back-propagate the score of a diffusion model through the Jacobian of a differentiable renderer, which we instantiate to be a voxel radiance field.
SDFusion: Multimodal 3D Shape Completion, Reconstruction, and Generation
yccyenchicheng/SDFusion
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CVPR 2023
To enable interactive generation, our method supports a variety of input modalities that can be easily provided by a human, including images, text, partially observed shapes and combinations of these, further allowing to adjust the strength of each input.
Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation
KU-CVLAB/3DFuse
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Text-to-3D generation has shown rapid progress in recent days with the advent of score distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural radiance field (NeRF) in the zero-shot setting.
Vox-E: Text-guided Voxel Editing of 3D Objects
TAU-VAILab/Vox-E
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ICCV 2023
Our method takes oriented 2D images of a 3D object as input and learns a grid-based volumetric representation of it.
Text2Room: Extracting Textured 3D Meshes from 2D Text-to-Image Models
lukashoel/text2room
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ICCV 2023
We present Text2Room, a method for generating room-scale textured 3D meshes from a given text prompt as input.
Set-the-Scene: Global-Local Training for Generating Controllable NeRF Scenes
We show that using proxies allows a wide variety of editing options, such as adjusting the placement of each independent object, removing objects from a scene, or refining an object.
Debiasing Scores and Prompts of 2D Diffusion for View-consistent Text-to-3D Generation
threestudio-project/threestudio
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NeurIPS 2023
In this work, we explore existing frameworks for score-distilling text-to-3D generation and identify the main causes of the view inconsistency problem -- the embedded bias of 2D diffusion models.
Re-imagine the Negative Prompt Algorithm: Transform 2D Diffusion into 3D, alleviate Janus problem and Beyond
ashawkey/stable-dreamfusion
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Although text-to-image diffusion models have made significant strides in generating images from text, they are sometimes more inclined to generate images like the data on which the model was trained rather than the provided text.
