Text to 3D

55 papers with code • 1 benchmarks • 1 datasets

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Use these libraries to find Text to 3D models and implementations


Most implemented papers

DreamFusion: Text-to-3D using 2D Diffusion

ashawkey/stable-dreamfusion 29 Sep 2022

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.

Latent-NeRF for Shape-Guided Generation of 3D Shapes and Textures

eladrich/latent-nerf CVPR 2023

This unique combination of text and shape guidance allows for increased control over the generation process.

Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Prior

junshutang/Make-It-3D ICCV 2023

In this work, we investigate the problem of creating high-fidelity 3D content from only a single image.

ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation

threestudio-project/threestudio NeurIPS 2023

In comparison, VSD works well with various CFG weights as ancestral sampling from diffusion models and simultaneously improves the diversity and sample quality with a common CFG weight (i. e., $7. 5$).

SyncDreamer: Generating Multiview-consistent Images from a Single-view Image

liuyuan-pal/syncdreamer 7 Sep 2023

In this paper, we present a novel diffusion model called that generates multiview-consistent images from a single-view image.

GeoDream: Disentangling 2D and Geometric Priors for High-Fidelity and Consistent 3D Generation

baaivision/GeoDream 29 Nov 2023

We justify that the refined 3D geometric priors aid in the 3D-aware capability of 2D diffusion priors, which in turn provides superior guidance for the refinement of 3D geometric priors.

Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splatting

WU-CVGL/MVControl-threestudio 15 Mar 2024

Building upon our MVControl architecture, we employ a unique hybrid diffusion guidance method to direct the optimization process.

DreamView: Injecting View-specific Text Guidance into Text-to-3D Generation

isee-laboratory/dreamview 9 Apr 2024

Text-to-3D generation, which synthesizes 3D assets according to an overall text description, has significantly progressed.

Intelligent Home 3D: Automatic 3D-House Design from Linguistic Descriptions Only

chenqi008/HPGM CVPR 2020

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).