Papers 3D Shape Modeling
“3D Shape Modeling” 태그가 달린 논문 30편 · 필터 해제
LoG3D: Ultra-High-Resolution 3D Shape Modeling via Local-to-Global Partitioning
Generating high-fidelity 3D contents remains a fundamental challenge due to the complexity of representing arbitrary topologies-such as open surfaces and intricate internal structures-while preserving geometric details. …
3D Shape ModelingBeyond Heuristics: Globally Optimal Configuration of Implicit Neural Representations
Implicit Neural Representations (INRs) have emerged as a transformative paradigm in signal processing and computer vision, excelling in tasks from image reconstruction to 3D shape modeling. Yet their effectiveness is fun…
Image Reconstruction3D Shape ModelingDirect3D-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+3SparseFlex: 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 RepresentationDora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
Recent 3D content generation pipelines commonly employ Variational Autoencoders (VAEs) to encode shapes into compact latent representations for diffusion-based generation. However, the widely adopted uniform point sampli…
3D Shape ModelingBenchmarking3D-WAG: Hierarchical Wavelet-Guided Autoregressive Generation for High-Fidelity 3D Shapes
Autoregressive (AR) models have achieved remarkable success in natural language and image generation, but their application to 3D shape modeling remains largely unexplored. Unlike diffusion models, AR models enable more …
3D Shape ModelingImage GenerationWeight Conditioning for Smooth Optimization of Neural Networks
In this article, we introduce a novel normalization technique for neural network weight matrices, which we term weight conditioning. This approach aims to narrow the gap between the smallest and largest singular values o…
3D Shape ModelingNeRFEfficient 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 CompletionTetSphere Splatting: Representing High-Quality Geometry with Lagrangian Volumetric Meshes
We introduce TetSphere Splatting, a Lagrangian geometry representation designed for high-quality 3D shape modeling. TetSphere splatting leverages an underused yet powerful geometric primitive -- volumetric tetrahedral me…
3D Generation3D Reconstruction3D Shape ModelingComputational Efficiency+4Efficient Learning With Sine-Activated Low-rank Matrices
Low-rank decomposition has emerged as a vital tool for enhancing parameter efficiency in neural network architectures, gaining traction across diverse applications in machine learning. These techniques significantly lowe…
3D Shape ModelingNeRFNeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generation
3D shape generation aims to produce innovative 3D content adhering to specific conditions and constraints. Existing methods often decompose 3D shapes into a sequence of localized components, treating each element in isol…
3D Shape Generation3D Shape ModelingTemporal 3D Shape Modeling for Video-Based Cloth-Changing Person Re-Identification
Video-based Cloth-Changing Person Re-ID (VCCRe-ID) refers to a real-world Re-ID problem where texture information like appearance or clothing becomes unreliable in long-term, limiting the applicability of traditional Re-…
3D Shape ModelingCloth-Changing Person Re-IdentificationPerson Re-IdentificationArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation
Due to advancements in infrastructural modulations, architectural design is one of the most peculiar and tedious processes. As the technology evolves to the next phase, using some latest techniques like generative advers…
3D Architecture3D Depth Estimation3D Semantic Scene Completion from a single 2D image3D Shape Modeling+63D VR Sketch Guided 3D Shape Prototyping and Exploration
3D shape modeling is labor-intensive, time-consuming, and requires years of expertise. To facilitate 3D shape modeling, we propose a 3D shape generation network that takes a 3D VR sketch as a condition. We assume that sk…
3D Shape Generation3D Shape Modeling3D Shape RepresentationTUVF: Learning Generalizable Texture UV Radiance Fields
Textures are a vital aspect of creating visually appealing and realistic 3D models. In this paper, we study the problem of generating high-fidelity texture given shapes of 3D assets, which has been relatively less explor…
3D Shape ModelingTexture SynthesisAttention-based Part Assembly for 3D Volumetric Shape Modeling
Modeling a 3D volumetric shape as an assembly of decomposed shape parts is much more challenging, but semantically more valuable than direct reconstruction from a full shape representation. The neural network needs to im…
3D Shape ModelingLoRD: Local 4D Implicit Representation for High-Fidelity Dynamic Human Modeling
Recent progress in 4D implicit representation focuses on globally controlling the shape and motion with low dimensional latent vectors, which is prone to missing surface details and accumulating tracking error. While man…
3D Shape Modeling4D reconstructionVocal Bursts Intensity Prediction3DILG: Irregular Latent Grids for 3D Generative Modeling
We propose a new representation for encoding 3D shapes as neural fields. The representation is designed to be compatible with the transformer architecture and to benefit both shape reconstruction and shape generation. Ex…
3D Shape ModelingA Temporal Learning Approach to Inpainting Endoscopic Specularities and Its effect on Image Correspondence
Video streams are utilised to guide minimally-invasive surgery and diagnostic procedures in a wide range of procedures, and many computer assisted techniques have been developed to automatically analyse them. These appro…
3D Reconstruction3D Shape ModelingAnatomyDiagnostic+5SPAGHETTI: Editing Implicit Shapes Through Part Aware Generation
Neural implicit fields are quickly emerging as an attractive representation for learning based techniques. However, adopting them for 3D shape modeling and editing is challenging. We introduce a method for $\mathbf{E}$di…
3D Shape Modeling