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3D Shape Representation

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Showing 51–92 of 92 papers

TitleStatusHype
Y^2Seq2Seq: Cross-Modal Representation Learning for 3D Shape and Text by Joint Reconstruction and Prediction of View and Word Sequences—0
3DMaterialGAN: Learning 3D Shape Representation from Latent Space for Materials Science Applications—0
3D Shape Synthesis for Conceptual Design and Optimization Using Variational Autoencoders—0
Adaptive Wavelet Transformer Network for 3D Shape Representation Learning—0
A generalized parametric 3D shape representation for articulated pose estimation—0
A Point Cloud Generative Model via Tree-Structured Graph Convolutions for 3D Brain Shape Reconstruction—0
ArcGAN: Generative Adversarial Networks for 3D Architectural Image Generation—0
Cloud Sphere: A 3D Shape Representation via Progressive Deformation—0
CN-DHF: Compact Neural Double Height-Field Representations of 3D Shapes—0
Contrastive Learning of 3D Shape Descriptor with Dynamic Adversarial Views—0
CoordX: Accelerating Implicit Neural Representation with a Split MLP Architecture—0
Data-Efficient Learning for Sim-to-Real Robotic Grasping using Deep Point Cloud Prediction Networks—0
Deep Level Sets: Implicit Surface Representations for 3D Shape Inference—0
Deep Sketch-Shape Hashing With Segmented 3D Stochastic Viewing—0
DiffHuman: Probabilistic Photorealistic 3D Reconstruction of Humans—0
Directionally Convolutional Networks for 3D Shape Segmentation—0
Dual Mesh Convolutional Networks for Human Shape Correspondence—0
DUDE: Deep Unsigned Distance Embeddings for Hi-Fidelity Representation of Complex 3D Surfaces—0
Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries—0
GarmentNets: Category-Level Pose Estimation for Garments via Canonical Space Shape Completion—0
Generative AI-based Prompt Evolution Engineering Design Optimization With Vision-Language Model—0
Geometric Disentanglement for Generative Latent Shape Models—0
Grounding Language Attributes to Objects using Bayesian Eigenobjects—0
GVCNN: Group-View Convolutional Neural Networks for 3D Shape Recognition—0
Hybrid Neural Diffeomorphic Flow for Shape Representation and Generation via Triplane—0
HybridSDF: Combining Deep Implicit Shapes and Geometric Primitives for 3D Shape Representation and Manipulation—0
Learning Attentive and Hierarchical Representations for 3D Shape Recognition—0
Learning Canonical Shape Space for Category-Level 6D Object Pose and Size Estimation—0
Learning Clothing and Pose Invariant 3D Shape Representation for Long-Term Person Re-Identification—0
Learning Occupancy Function from Point Clouds for Surface Reconstruction—0
Learning Spatially Collaged Fourier Bases for Implicit Neural Representation—0
Local Implicit Grid Representations for 3D Scenes—0
MASH: Masked Anchored SpHerical Distances for 3D Shape Representation and Generation—0
MIRE: Matched Implicit Neural Representations—0
Mosaic-SDF for 3D Generative Models—0
Multiplicative Fourier Level of Detail—0
Multiresolution Deep Implicit Functions for 3D Shape Representation—0
Multi-View Photometric Stereo Revisited—0
NeuralODF: Learning Omnidirectional Distance Fields for 3D Shape Representation—0
Novel View Synthesis from Single Images via Point Cloud Transformation—0
OmniNeRF: Hybriding Omnidirectional Distance and Radiance fields for Neural Surface Reconstruction—0
Planes vs. Chairs: Category-guided 3D shape learning without any 3D cues—0
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