Recent advances in 3d gaussian splatting
The emergence of 3D Gaussian splatting (3DGS) has greatly accelerated rendering in novel
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …
view synthesis. Unlike neural implicit representations like neural radiance fields (NeRFs) …
Deep generative models in engineering design: A review
Automated design synthesis has the potential to revolutionize the modern engineering
design process and improve access to highly optimized and customized products across …
design process and improve access to highly optimized and customized products across …
Latent-nerf for shape-guided generation of 3d shapes and textures
Text-guided image generation has progressed rapidly in recent years, inspiring major
breakthroughs in text-guided shape generation. Recently, it has been shown that using …
breakthroughs in text-guided shape generation. Recently, it has been shown that using …
Lion: Latent point diffusion models for 3d shape generation
Denoising diffusion models (DDMs) have shown promising results in 3D point cloud
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …
synthesis. To advance 3D DDMs and make them useful for digital artists, we require (i) high …
Dream3d: Zero-shot text-to-3d synthesis using 3d shape prior and text-to-image diffusion models
Recent CLIP-guided 3D optimization methods, such as DreamFields and PureCLIPNeRF,
have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch …
have achieved impressive results in zero-shot text-to-3D synthesis. However, due to scratch …
Deep marching tetrahedra: a hybrid representation for high-resolution 3d shape synthesis
We introduce DMTet, a deep 3D conditional generative model that can synthesize high-
resolution 3D shapes using simple user guides such as coarse voxels. It marries the merits …
resolution 3D shapes using simple user guides such as coarse voxels. It marries the merits …
Let 2d diffusion model know 3d-consistency for robust text-to-3d generation
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 …
distillation, a methodology of using pretrained text-to-2D diffusion models to optimize neural …
Local deep implicit functions for 3d shape
The goal of this project is to learn a 3D shape representation that enables accurate surface
reconstruction, compact storage, efficient computation, consistency for similar shapes …
reconstruction, compact storage, efficient computation, consistency for similar shapes …
Learning gradient fields for shape generation
In this work, we propose a novel technique to generate shapes from point cloud data. A point
cloud can be viewed as samples from a distribution of 3D points whose density is …
cloud can be viewed as samples from a distribution of 3D points whose density is …
Towards implicit text-guided 3d shape generation
In this work, we explore the challenging task of generating 3D shapes from text. Beyond the
existing works, we propose a new approach for text-guided 3D shape generation, capable of …
existing works, we propose a new approach for text-guided 3D shape generation, capable of …