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Point Cloud Generation
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논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Simultaneous Localization and Mapping Using Active mmWave Sensing in 5G NR
RaGNNarok: A Light-Weight Graph Neural Network for Enhancing Radar Point Clouds on Unmanned Ground Vehicles
SIM-Net: A Multimodal Fusion Network Using Inferred 3D Object Shape Point Clouds from RGB Images for 2D Classification
A Strong View-Free Baseline Approach for Single-View Image Guided Point Cloud Completion
Toward Patient-specific Partial Point Cloud to Surface Completion for Pre- to Intra-operative Registration in Image-guided Liver Interventions
Flexible-weighted Chamfer Distance: Enhanced Objective Function for Point Cloud Completion
TopoDiT-3D: Topology-Aware Diffusion Transformer with Bottleneck Structure for 3D Point Cloud Generation
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene Understanding
RefComp: A Reference-guided Unified Framework for Unpaired Point Cloud Completion
Robust Unsupervised Domain Adaptation for 3D Point Cloud Segmentation Under Source Adversarial Attacks
SymmCompletion: High-Fidelity and High-Consistency Point Cloud Completion with Symmetry Guidance
Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priors
SuperPC: A Single Diffusion Model for Point Cloud Completion, Upsampling, Denoising, and Colorization
Parametric Point Cloud Completion for Polygonal Surface Reconstruction
3D Point Cloud Generation via Autoregressive Up-sampling
EAGLE: Contextual Point Cloud Generation via Adaptive Continuous Normalizing Flow with Self-Attention
DDEQs: Distributional Deep Equilibrium Models through Wasserstein Gradient Flows
GenPC: Zero-shot Point Cloud Completion via 3D Generative Priors
PointSea: Point Cloud Completion via Self-structure Augmentation
Imagine with the Teacher: Complete Shape in a Multi-View Distillation Way
MambaTron: Efficient Cross-Modal Point Cloud Enhancement using Aggregate Selective State Space Modeling
DC-PCN: Point Cloud Completion Network with Dual-Codebook Guided Quantization
Generative diffusion model with inverse renormalization group flows
DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion
ObitoNet: Multimodal High-Resolution Point Cloud Reconstruction
Hyperbolic Chamfer Distance for Point Cloud Completion and Beyond
Position-aware Guided Point Cloud Completion with CLIP Model
Digging into Intrinsic Contextual Information for High-fidelity 3D Point Cloud Completion
PointCFormer: a Relation-based Progressive Feature Extraction Network for Point Cloud Completion
LiDAR-EDIT: LiDAR Data Generation by Editing the Object Layouts in Real-World Scenes
PCDreamer: Point Cloud Completion Through Multi-view Diffusion Priors
Revisiting Point Cloud Completion: Are We Ready For The Real-World?
Learning 3D Representations from Procedural 3D Programs
SPAC-Net: Rethinking Point Cloud Completion with Structural Prior
PocoLoco: A Point Cloud Diffusion Model of Human Shape in Loose Clothing
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.