Point cloud reconstruction
36 papers with code • 0 benchmarks • 0 datasets
This task aims to solve inherent problems in raw point clouds: sparsity, noise, and irregularity.
Benchmarks
These leaderboards are used to track progress in Point cloud reconstruction
Most implemented papers
SO-Net: Self-Organizing Network for Point Cloud Analysis
This paper presents SO-Net, a permutation invariant architecture for deep learning with orderless point clouds.
YOLO3D: End-to-end real-time 3D Oriented Object Bounding Box Detection from LiDAR Point Cloud
maudzung/YOLO3D-YOLOv4-PyTorch
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LiDAR sensors are employed to provide the 3D point cloud reconstruction of the surrounding environment, while the task of 3D object bounding box detection in real time remains a strong algorithmic challenge.
Dense Hybrid Recurrent Multi-view Stereo Net with Dynamic Consistency Checking
yhw-yhw/D2HC-RMVSNet
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ECCV 2020
In this paper, we propose an efficient and effective dense hybrid recurrent multi-view stereo net with dynamic consistency checking, namely $D^{2}$HC-RMVSNet, for accurate dense point cloud reconstruction.
PointMixer: MLP-Mixer for Point Cloud Understanding
lifebeyondexpectations/eccv22-pointmixer
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MLP-Mixer has newly appeared as a new challenger against the realm of CNNs and transformer.
3D-LMNet: Latent Embedding Matching for Accurate and Diverse 3D Point Cloud Reconstruction from a Single Image
3D reconstruction from single view images is an ill-posed problem.
3D-PSRNet: Part Segmented 3D Point Cloud Reconstruction From a Single Image
We propose a mechanism to reconstruct part annotated 3D point clouds of objects given just a single input image.
CAPNet: Continuous Approximation Projection For 3D Point Cloud Reconstruction Using 2D Supervision
val-iisc/capnet
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We consider the task of single image 3D point cloud reconstruction, and aim to utilize multiple foreground masks as our supervisory data to alleviate the need for large scale 3D datasets.
Dense 3D Point Cloud Reconstruction Using a Deep Pyramid Network
Through extensive quantitative and qualitative evaluation on synthetic and real datasets, we demonstrate that DensePCR outperforms the existing state-of-the-art point cloud reconstruction works, while also providing a light-weight and scalable architecture for predicting high-resolution outputs.
Silhouette Guided Point Cloud Reconstruction beyond Occlusion
zouchuhang/Silhouette-Guided-3D
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One major challenge in 3D reconstruction is to infer the complete shape geometry from partial foreground occlusions.
Pyramid Multi-view Stereo Net with Self-adaptive View Aggregation
yhw-yhw/PVAMVSNet
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ECCV 2020
n this paper, we propose an effective and efficient pyramid multi-view stereo (MVS) net with self-adaptive view aggregation for accurate and complete dense point cloud reconstruction.
