GitHub - Runkun-Lu/multi_view-learning-summarize: I am doing some research about multi-view learning and I want to make a summarize about my work.

Some papers and its corresponding source code:

DeepMVS: Learning Multi-View Stereopsis. (paper, code&data)
Multi-view Face Detection Using Deep Convolutional Neural Networks. (paper, code1, code2, code3)
Multi-view Convolutional Neural Networks for 3D Shape Recognition. (paper, code)
Partial Multi-View Clustering Using Graph Regularized NMF. (paper, code)
Multiple View Geometry in Computer Vision. (paper, code)
Multi-view low-rank sparse subspace clustering. (paper, code)
Vehicle Pose and Shape Estimation through Multiple Monocular Vision. (paper, code)
Binary Multi-View Clustering. (paper, code)
A unifying framework for vector-valued manifold regularization and multi-view learning. (paper, code)
Matching People across Camera Views using Kernel Canonical Correlation Analysis. (paper, code)
Multi Channel-Kernel Canonical Correlation Analysis for Cross-View Person Re-Identification. (paper, code)
Multiple Incomplete Views Clustering via Weighted Nonnegative Matrix Factorization with L2,1 Regularization. (paper, code)
Multi-view clustering. (paper, code(matlab, R))
Online Multi-view Clustering with Incomplete Views. (paper, code)
Online Unsupervised Multi-view Feature Selection. (paper, code)
Heterogeneous image feature integration via multi-modal spectral clustering. (paper, code)
Robust Multi-View Spectral Clustering via Low-Rank and Sparse Decomposition. (paper, code)
Projective Feature Learning for 3D Shapes with Multi-View Depth Images. (paper, code)
Multi-View Clustering and Feature Learning via Structured Sparsity. (paper, code)
Large-Scale Multi-View Spectral Clustering via Bipartite Graph. (paper, code)
Feature extraction via multi-view non-negative matrix factorization with local graph regularization. (paper, code)
Partial Multi-view Outlier Detection Based on Collective Learning. (paper, code)
Incomplete Multi-view Clustering via Graph Regularized Matrix Factorization. (paper, code)
Local kernel alignment based multi-view clustering using extreme learning machine. (paper, code)
Reconstructing Perceived Images From Human Brain Activities With Bayesian Deep Multiview Learning. (paper, code)
Multi-View Dynamic Facial Action Unit Detection. (paper, code)
Constrained Multi-View Video Face Clustering. (paper, code)
Consistent and Specific Multi-view Subspace Clustering. (paper, code)
Multi-View Clustering via Deep Matrix Factorization. (paper, code)
COMIC: Multi-view Clustering Without Parameter Selection. (paper, code)
Neural News Recommendation with Attentive Multi-View Learning. (paper, code)
MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation. (paper, code)
COMIC: Multi-view Clustering Without Parameter Selection. (paper, code)
Multi-view Deep Subspace Clustering Network. (paper, code)