3D Shape Representation

37 papers with code • 0 benchmarks • 4 datasets

Image: MeshNet

EXIM: A Hybrid Explicit-Implicit Representation for Text-Guided 3D Shape Generation

liuzhengzhe/exim 3 Nov 2023

This paper presents a new text-guided technique for generating 3D shapes.

22
03 Nov 2023

RayDF: Neural Ray-surface Distance Fields with Multi-view Consistency

vlar-group/raydf NeurIPS 2023

In this paper, we study the problem of continuous 3D shape representations.

101
30 Oct 2023

ASUR3D: Arbitrary Scale Upsampling and Refinement of 3D Point Clouds using Local Occupancy Fields

Akash-Kumbar/ASUR3D IEEE/CVF International Conference on Computer Vision Workshops (ICCVW) 2023

Our proposed implicit occupancy representation enables efficient point classification, effectively discerning points belonging to the surface from non-surface points.

0
02 Oct 2023

On the Localization of Ultrasound Image Slices within Point Distribution Models

vuenc/slice-to-shape 1 Sep 2023

We demonstrate that our multi-modal registration framework can localize images on the 3D surface topology of a patient-specific organ and the mean shape of an SSM.

1
01 Sep 2023

3D Semantic Subspace Traverser: Empowering 3D Generative Model with Shape Editing Capability

TrepangCat/3D_Semantic_Subspace_Traverser ICCV 2023

Our method utilizes implicit functions as the 3D shape representation and combines a novel latent-space GAN with a linear subspace model to discover semantic dimensions in the local latent space of 3D shapes.

63
26 Jul 2023

3D VR Sketch Guided 3D Shape Prototyping and Exploration

rowl1ng/3dsketch2shape ICCV 2023

3D shape modeling is labor-intensive, time-consuming, and requires years of expertise.

13
19 Jun 2023

OpenShape: Scaling Up 3D Shape Representation Towards Open-World Understanding

Colin97/OpenShape_code NeurIPS 2023

Due to their alignment with CLIP embeddings, our learned shape representations can also be integrated with off-the-shelf CLIP-based models for various applications, such as point cloud captioning and point cloud-conditioned image generation.

191
18 May 2023

3DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Models

1zb/3dshape2vecset 26 Jan 2023

We introduce 3DShape2VecSet, a novel shape representation for neural fields designed for generative diffusion models.

147
26 Jan 2023

SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation

zhengxinyang/sdf-stylegan 24 Jun 2022

We further complement the evaluation metrics of 3D generative models with the shading-image-based Fr\'echet inception distance (FID) scores to better assess visual quality and shape distribution of the generated shapes.

111
24 Jun 2022