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Point cloud reconstruction
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This task aims to solve inherent problems in raw point clouds: sparsity, noise, and irregularity.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Curve-Aware Gaussian Splatting for 3D Parametric Curve Reconstruction
DiffS-NOCS: 3D Point Cloud Reconstruction through Coloring Sketches to NOCS Maps Using Diffusion Models
Less is More: Efficient Point Cloud Reconstruction via Multi-Head Decoders
Estimating the Diameter at Breast Height of Trees in a Forest With a Single 360 Camera
GarmentGS: Point-Cloud Guided Gaussian Splatting for High-Fidelity Non-Watertight 3D Garment Reconstruction
SC-NeRF: NeRF-based Point Cloud Reconstruction using a Stationary Camera for Agricultural Applications
AIM2PC: Aerial Image to 3D Building Point Cloud Reconstruction
R2LDM: An Efficient 4D Radar Super-Resolution Framework Leveraging Diffusion Model
Dynamic Point Maps: A Versatile Representation for Dynamic 3D Reconstruction
VGGT: Visual Geometry Grounded Transformer
Consistency Diffusion Models for Single-Image 3D Reconstruction with Priors
MambaTron: Efficient Cross-Modal Point Cloud Enhancement using Aggregate Selective State Space Modeling
BloomScene: Lightweight Structured 3D Gaussian Splatting for Crossmodal Scene Generation
ObitoNet: Multimodal High-Resolution Point Cloud Reconstruction
DSRC: Learning Density-insensitive and Semantic-aware Collaborative Representation against Corruptions
Hyperbolic-constraint Point Cloud Reconstruction from Single RGB-D Images
CrossSDF: 3D Reconstruction of Thin Structures From Cross-Sections
SPACE: 3D Spatial Co-operation and Exploration Framework for Robust Mapping and Coverage with Multi-Robot Systems
MultiPull: Detailing Signed Distance Functions by Pulling Multi-Level Queries at Multi-Step
Constrained Diffusion Implicit Models
LiVisSfM: Accurate and Robust Structure-from-Motion with LiDAR and Visual Cues
Diffusion Models in 3D Vision: A Survey
Learning Local Pattern Modularization for Point Cloud Reconstruction from Unseen Classes
DG-PIC: Domain Generalized Point-In-Context Learning for Point Cloud Understanding
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion
APC2Mesh: Bridging the gap from occluded building façades to full 3D models
Unsupervised Occupancy Learning from Sparse Point Cloud
Few-shot point cloud reconstruction and denoising via learned Guassian splats renderings and fine-tuned diffusion features
PSS-BA: LiDAR Bundle Adjustment with Progressive Spatial Smoothing
GEM3D: GEnerative Medial Abstractions for 3D Shape Synthesis
DiffPoint: Single and Multi-view Point Cloud Reconstruction with ViT Based Diffusion Model
Headset: Human emotion awareness under partial occlusions multimodal dataset
Learnable Chamfer Distance for Point Cloud Reconstruction
DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstruction
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.