Face Clustering
21 papers with code • 1 benchmarks • 3 datasets
Face Clustering in the videos
Libraries
Use these libraries to find Face Clustering models and implementations
EasyCom
MovieGraphs
A View From Somewhere (AVFS)
Latest papers with no code
Clustering based Contrastive Learning for Improving Face Representations
We demonstrate our method on the challenging task of learning representations for video face clustering.
Constructing the F-Graph with a Symmetric Constraint for Subspace Clustering
Based on further studying the low-rank subspace clustering (LRSC) and L2-graph subspace clustering algorithms, we propose a F-graph subspace clustering algorithm with a symmetric constraint (FSSC), which constructs a new objective function with a symmetric constraint basing on F-norm, whose the most significant advantage is to obtain a closed-form solution of the coefficient matrix.
Subspace Clustering with Active Learning
In this paper, we propose an active learning framework for subspace clustering that sequentially queries informative points and updates the subspace model.
Robust Subspace Clustering With Independent and Piecewise Identically Distributed Noise Modeling
In this work, we propose an independent and piecewise identically distributed (i. p. i. d.)
Robust Kernelized Multi-View Self-Representations for Clustering by Tensor Multi-Rank Minimization
In particular, the original tensor-based multi-view self-representation clustering problem is a special case of our approach and can be solved by our algorithm.
Community Recovery in Hypergraphs
The objective of the problem is to cluster data points into distinct communities based on a set of measurements, each of which is associated with the values of a certain number of data points.
Face Clustering: Representation and Pairwise Constraints
Given this representation, we design a clustering algorithm, Conditional Pairwise Clustering (ConPaC), which directly estimates the adjacency matrix only based on the similarity between face images.
Subspace Clustering via Optimal Direction Search
This letter presents a new spectral-clustering-based approach to the subspace clustering problem.
A Proximity-Aware Hierarchical Clustering of Faces
In this paper, we propose an unsupervised face clustering algorithm called "Proximity-Aware Hierarchical Clustering" (PAHC) that exploits the local structure of deep representations.
Outlier Cluster Formation in Spectral Clustering
The highlights of this paper are the following two mathematical observations: first, spectral clustering's intrinsic property of an outlier cluster formation, and second, the singularity of an outlier cluster with a valid cluster number.
