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3D Shape Representation

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Papers

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Showing 51–92 of 92 papers

TitleStatusHype
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
Planes vs. Chairs: Category-guided 3D shape learning without any 3D cues—0
Self-supervised Graph Neural Network for Mechanical CAD Retrieval—0
Self-supervised Learning of Implicit Shape Representation with Dense Correspondence for Deformable Objects—0
SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modeling—0
TAMM: TriAdapter Multi-Modal Learning for 3D Shape Understanding—0
Taylor3DNet: Fast 3D Shape Inference With Landmark Points Based Taylor Series—0
TIFu: Tri-directional Implicit Function for High-Fidelity 3D Character Reconstruction—0
Training Data Generating Networks: Shape Reconstruction via Bi-level Optimization—0
3DFaceGAN: Adversarial Nets for 3D Face Representation, Generation, and Translation—0
Learning Discriminative 3D Shape Representations by View Discerning NetworksCode0
Local Deep Implicit Functions for 3D ShapeCode0
ASUR3D: Arbitrary Scale Upsampling and Refinement of 3D Point Clouds using Local Occupancy FieldsCode0
Towards the Evolution of Vertical-Axis Wind Turbines using SupershapesCode0
On the Localization of Ultrasound Image Slices within Point Distribution ModelsCode0
Neural 3D Morphable Models: Spiral Convolutional Networks for 3D Shape Representation Learning and GenerationCode0
MeshNet: Mesh Neural Network for 3D Shape RepresentationCode0
LP-DIF: Learning Local Pattern-Specific Deep Implicit Function for 3D Objects and ScenesCode0
Local Implicit Grid Representations for 3D ScenesCode0
3D Point Capsule NetworksCode0
Learning Implicit Fields for Generative Shape ModelingCode0
PVNet: A Joint Convolutional Network of Point Cloud and Multi-View for 3D Shape RecognitionCode0
Learning Embedding of 3D models with Quadric LossCode0
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