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aanet

AANet: Adaptive Aggregation Network for Efficient Stereo Matching, CVPR 2020

al_lidar_cls

awesome-learning-mvs

A list of awesome learning-based multi-view stereo papers

awesome-point-cloud-analysis

A list of papers and datasets about point cloud analysis (processing)

awesome-point-cloud-registration

A curated list of point cloud registration.

awesome-self-supervised-learning

A curated list of awesome self-supervised methods

awesome-self-supervised-learning-on-3d

Paper list for anyone who are interested in self-supervised learning on 3D point cloud.

awesome-semantic-segmentation

:metal: awesome-semantic-segmentation

awesome-slam-datasets

A curated list of awesome datasets for SLAM

awesome_3dreconstruction_list

A curated list of papers & resources linked to 3D reconstruction from images.

cvp-mvsnet

Cost Volume Pyramid Based Depth Inference for Multi-View Stereo

densematchingbenchmark

Dense Matching Benchmark

fair_self_supervision_benchmark

Scaling and Benchmarking Self-Supervised Visual Representation Learning

high-res-stereo

Hierarchical Deep Stereo Matching on High Resolution Images, CVPR 2019.

patchmatchstereo

PatchMatchStereo，倾斜窗口经典，效果极佳，OpenMVS&Colmap稠密匹配算法。完整实现，代码规范，注释清晰，博客教学，欢迎star！

pc2pix

Keras code of my 2019 CVPR Workshop paper "A Conditional Generative Adversarial Network for Rendering Point Clouds"

pixel-level-contrastive-learning

Implementation of Pixel-level Contrastive Learning, proposed in the paper "Propagate Yourself", in Pytorch

pointcloudengine

Point Cloud Rendering Engine with Octree Generation, Splat Blending, Phong Lighting and Neural Network Evaluation

pointmvsnet

Code for "Point-based Multi-view Stereo Network" (ICCV 2019 Oral) & "Visibility-aware Point-based Multi-view Stereo Network" (TPAMI)

pycontrast

PyTorch implementation of Contrastive Learning methods; List of awesome-contrastive-learning papers

scanobjectnn

Code for Revisiting Point Cloud Classification: A New Benchmark Dataset and Classification Model on Real-World Data, ICCV 2019

self-supervised-mvs

Pytorch codes for "Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation"

semiglobalmatching

SGM，立体匹配StereoMatching最经典应用最广泛算法，4000+引用，兼顾效率和效果。完整实现，代码规范，注释清晰，博客教学，欢迎star！

sensaturban

🔥Urban-scale point cloud dataset (Arxiv'2020)

torch-points3d

Pytorch framework for doing deep learning on point clouds.

torch3d

Datasets, networks and transformations for 3D deep learning in PyTorch