Papers 3D Shape Generation
“3D Shape Generation” 태그가 달린 논문 105편 · 필터 해제
3D Shape Generation: A Survey
Recent advances in deep learning have significantly transformed the field of 3D shape generation, enabling the synthesis of complex, diverse, and semantically meaningful 3D objects. This survey provides a comprehensive o…
3D Shape GenerationDiversitySurveyLTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework
We present LTM3D, a Latent Token space Modeling framework for conditional 3D shape generation that integrates the strengths of diffusion and auto-regressive (AR) models. While diffusion-based methods effectively model co…
3D Generation3D Shape GenerationDirect3D-S2: Gigascale 3D Generation Made Easy with Spatial Sparse Attention
Generating high-resolution 3D shapes using volumetric representations such as Signed Distance Functions (SDFs) presents substantial computational and memory challenges. We introduce Direct3D-S2, a scalable 3D generation …
3D Generation3D geometry3D Object Reconstruction3D Reconstruction+3OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generation
Autoregressive models have achieved remarkable success across various domains, yet their performance in 3D shape generation lags significantly behind that of diffusion models. In this paper, we introduce OctGPT, a novel …
3D Shape GenerationSparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling
Creating high-fidelity 3D meshes with arbitrary topology, including open surfaces and complex interiors, remains a significant challenge. Existing implicit field methods often require costly and detail-degrading watertig…
3D Shape Generation3D Shape Modeling3D Shape RepresentationARMO: Autoregressive Rigging for Multi-Category Objects
Recent advancements in large-scale generative models have significantly improved the quality and diversity of 3D shape generation. However, most existing methods focus primarily on generating static 3D models, overlookin…
3D Shape GenerationConnectivity EstimationShape Generation via Weight Space Learning
Foundation models for 3D shape generation have recently shown a remarkable capacity to encode rich geometric priors across both global and local dimensions. However, leveraging these priors for downstream tasks can be ch…
3D Shape GenerationWeight Space LearningUnleashing Vecset Diffusion Model for Fast Shape Generation
3D shape generation has greatly flourished through the development of so-called "native" 3D diffusion, particularly through the Vecset Diffusion Model (VDM). While recent advancements have shown promising results in gene…
3D Generation3D Shape GenerationDecodermodel3D Shape Completion using Multi-Resolution Spectral Encoding
Reconstruction of intricate local patterns and large missing regions during 3D shape completion has the contradictory requirements of computation over a wider context and operations for finer detail restoration. To this …
3D Inpainting3D Shape Generation3D Shape ReconstructionPandora3D: A Comprehensive Framework for High-Quality 3D Shape and Texture Generation
This report presents a comprehensive framework for generating high-quality 3D shapes and textures from diverse input prompts, including single images, multi-view images, and text descriptions. The framework consists of 3…
3D Shape GenerationTexture SynthesisTripoSG: High-Fidelity 3D Shape Synthesis using Large-Scale Rectified Flow Models
Recent advancements in diffusion techniques have propelled image and video generation to unprecedented levels of quality, significantly accelerating the deployment and application of generative AI. However, 3D shape gene…
3D Generation3D Reconstruction3D Shape GenerationVideo GenerationShape from Semantics: 3D Shape Generation from Multi-View Semantics
We propose ``Shape from Semantics'', which is able to create 3D models whose geometry and appearance match given semantics when observed from different views. Traditional ``Shape from X'' tasks usually use visual input (…
3D geometry3D Shape GenerationImage RestorationVideo GenerationBAG: Body-Aligned 3D Wearable Asset Generation
While recent advancements have shown remarkable progress in general 3D shape generation models, the challenge of leveraging these approaches to automatically generate wearable 3D assets remains unexplored. To this end, w…
3D Generation3D Shape GenerationDiversityMulti-scale Latent Point Consistency Models for 3D Shape Generation
Consistency Models (CMs) have significantly accelerated the sampling process in diffusion models, yielding impressive results in synthesizing high-resolution images. To explore and extend these advancements to point-clou…
3D Shape GenerationDiversityParameterize Structure with Differentiable Template for 3D Shape Generation
Structural representation is crucial for reconstructing and generating editable 3D shapes with part semantics. Recent 3D shape generation works employ complicated networks and structure definitions relying on hierarchica…
3D Shape GenerationPoint Cloud GenerationGenCAD: Image-Conditioned Computer-Aided Design Generation with Transformer-Based Contrastive Representation and Diffusion Priors
The creation of manufacturable and editable 3D shapes through Computer-Aided Design (CAD) remains a highly manual and time-consuming task, hampered by the complex topology of boundary representations of 3D solids and uni…
3D Shape GenerationContrastive LearningRepresentation LearningOctFusion: Octree-based Diffusion Models for 3D Shape Generation
Diffusion models have emerged as a popular method for 3D generation. However, it is still challenging for diffusion models to efficiently generate diverse and high-quality 3D shapes. In this paper, we introduce OctFusion…
3D Generation3D Shape GenerationGPUAn Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion
We introduce a new approach for generating realistic 3D models with UV maps through a representation termed "Object Images." This approach encapsulates surface geometry, appearance, and patch structures within a 64x64 pi…
3D Shape GenerationImage GenerationObjectHOTS3D: Hyper-Spherical Optimal Transport for Semantic Alignment of Text-to-3D Generation
Recent CLIP-guided 3D generation methods have achieved promising results but struggle with generating faithful 3D shapes that conform with input text due to the gap between text and image embeddings. To this end, this pa…
3D Generation3D Shape GenerationDecoderNeRF+1Efficient 3D Shape Generation via Diffusion Mamba with Bidirectional SSMs
Recent advancements in sequence modeling have led to the development of the Mamba architecture, noted for its selective state space approach, offering a promising avenue for efficient long sequence handling. However, its…
3D Shape Generation3D Shape ModelingMambaPoint Cloud Completion