Text to 3D
13 papers with code • 0 benchmarks • 0 datasets
Benchmarks
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Libraries
Use these libraries to find Text to 3D models and implementationsMost implemented papers
DreamFusion: Text-to-3D using 2D Diffusion
ashawkey/stable-dreamfusion
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Using this loss in a DeepDream-like procedure, we optimize a randomly-initialized 3D model (a Neural Radiance Field, or NeRF) via gradient descent such that its 2D renderings from random angles achieve a low loss.
Fantasia3D: Disentangling Geometry and Appearance for High-quality Text-to-3D Content Creation
Key to Fantasia3D is the disentangled modeling and learning of geometry and appearance.
Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures
eladrich/latent-nerf
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CVPR 2023
This unique combination of text and shape guidance allows for increased control over the generation process.
ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation
threestudio-project/threestudio
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In this work, we propose to model the 3D parameter as a random variable instead of a constant as in SDS and present variational score distillation (VSD), a principled particle-based variational framework to explain and address the aforementioned issues in text-to-3D generation.
Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only
To this end, we propose a House Plan Generative Model (HPGM) that first translates the language input to a structural graph representation and then predicts the layout of rooms with a Graph Conditioned Layout Prediction Network (GC LPN) and generates the interior texture with a Language Conditioned Texture GAN (LCT-GAN).
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.
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.
ChatGPT is not all you need. A State of the Art Review of large Generative AI models
zhaoolee/garss
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During the last two years there has been a plethora of large generative models such as ChatGPT or Stable Diffusion that have been published.
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.
