https://github.com/yhw-yhw/PVAMVSNet
공식 코드Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
Papers with Code 아카이브
Point cloud reconstruction
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This task aims to solve inherent problems in raw point clouds: sparsity, noise, and irregularity.
코드
관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.
https://github.com/zhirui-gao/curve-gaussian
공식 코드Curve-Aware Gaussian Splatting for 3D Parametric Curve Reconstruction
https://github.com/zouchuhang/Silhouette-Guided-3D
공식 코드Silhouette Guided Point Cloud Reconstruction beyond Occlusion
https://github.com/zvict/papr
공식 코드https://github.com/LONG-9621/SO-Net
https://github.com/Ouasfi/Feat-NKRR-adaptation
Robustifying Generalizable Implicit Shape Networks with a Tunable Non-Parametric Model
https://github.com/Ouasfi/SparseOcc
https://github.com/RichardMinsooGo-ML/Pytorch-Yolo-3d-Yolov3
YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
https://github.com/RichardMinsooGo-ML/Pytorch-Yolo-3d-Yolov4
YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
https://github.com/donnyruixu/pc-elm-ae
https://github.com/haibao637/D2HC-RMVSNet
Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking
https://github.com/hrisi/tree-species-classification
https://github.com/maudzung/YOLO3D-YOLOv4-PyTorch
YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
https://github.com/nv-tlabs/XCube
fVDB: A Deep-Learning Framework for Sparse, Large-Scale, and High-Performance Spatial Intelligence
https://github.com/pbonazzi/guassian-diffusion
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.