https://github.com/kazuto1011/r2dm
공식 코드LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models
태스크의 하위 분류와 논문·코드·평가·기법·데이터셋을 탐색하세요.
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
LiDAR Data Synthesis with Denoising Diffusion Probabilistic Models
VET: Visual Error Tomography for Point Cloud Completion and High-Quality Neural Rendering
Leveraging Single-View Images for Unsupervised 3D Point Cloud Completion
Self-supervised 3D Point Cloud Completion via Multi-view Adversarial Learning
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
PointAttN: You Only Need Attention for Point Cloud Completion
Fine-Tuning Generative Models as an Inference Method for Robotic Tasks
Parametric Point Cloud Completion for Polygonal Surface Reconstruction
Point Cloud Diffusion Models for Automatic Implant Generation
TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network
PG-RCNN: Semantic Surface Point Generation for 3D Object Detection
Compositional Semantic Mix for Domain Adaptation in Point Cloud Segmentation
SPAC-Net: Rethinking Point Cloud Completion with Structural Prior
ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion
PocoLoco: A Point Cloud Diffusion Model of Human Shape in Loose Clothing
Towards realistic symmetry-based completion of previously unseen point clouds
Leveraging Automatic CAD Annotations for Supervised Learning in 3D Scene Understanding
CF-PRNet: Coarse-to-Fine Prototype Refining Network for Point Cloud Completion and Reconstruction
Explicitly Guided Information Interaction Network for Cross-modal Point Cloud Completion
Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion
Voxel-based Network for Shape Completion by Leveraging Edge Generation
Unpaired Point Cloud Completion on Real Scans using Adversarial Training
DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
PointSSC: A Cooperative Vehicle-Infrastructure Point Cloud Benchmark for Semantic Scene Completion
Loss Distillation via Gradient Matching for Point Cloud Completion with Weighted Chamfer Distance
PCKRF: Point Cloud Completion and Keypoint Refinement With Fusion Data for 6D Pose Estimation
A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.