Face Clustering

21 papers with code • 1 benchmarks • 3 datasets

Face Clustering in the videos


Use these libraries to find Face Clustering models and implementations

Most implemented papers

Sparse Subspace Clustering: Algorithm, Theory, and Applications

panji1990/Deep-subspace-clustering-networks 5 Mar 2012

In this paper, we propose and study an algorithm, called Sparse Subspace Clustering (SSC), to cluster data points that lie in a union of low-dimensional subspaces.

Linkage Based Face Clustering via Graph Convolution Network

Zhongdao/gcn_clustering CVPR 2019

The key idea is that we find the local context in the feature space around an instance (face) contains rich information about the linkage relationship between this instance and its neighbors.

Learning to Cluster Faces via Confidence and Connectivity Estimation

yl-1993/learn-to-cluster CVPR 2020

With the vertex confidence and edge connectivity, we can naturally organize more relevant vertices on the affinity graph and group them into clusters.

Scalable Sparse Subspace Clustering by Orthogonal Matching Pursuit

ChongYou/subspace-clustering CVPR 2016

Subspace clustering methods based on $\ell_1$, $\ell_2$ or nuclear norm regularization have become very popular due to their simplicity, theoretical guarantees and empirical success.


ankuPRK/COFC International Conference on Image Processing (ICIP) 2018

We address the problem of face clustering in long, real world videos. This is a challenging task because faces in such videos exhibit wid evariability in scale, pose, illumination, expressions, and may also be partially occluded.

Learning Hierarchical Graph Neural Networks for Image Clustering

dmlc/dgl ICCV 2021

Our hierarchical GNN uses a novel approach to merge connected components predicted at each level of the hierarchy to form a new graph at the next level.

Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space

damo-cv/ada-nets ICLR 2022

In Ada-NETS, each face is transformed to a new structure space, obtaining robust features by considering face features of the neighbour images.

Robust Subspace Clustering via Smoothed Rank Approximation

sckangz/logdet 18 Aug 2015

However, for many real-world applications, nuclear norm approximation to the rank function can only produce a result far from the optimum.

Shape Interaction Matrix Revisited and Robustified: Efficient Subspace Clustering with Corrupted and Incomplete Data

panji530/Robust-shape-interaction-matrix ICCV 2015

The Shape Interaction Matrix (SIM) is one of the earliest approaches to performing subspace clustering (i. e., separating points drawn from a union of subspaces).

Robust Subspace Clustering via Tighter Rank Approximation

sckangz/arctangent 30 Oct 2015

For this nonconvex minimization problem, we develop an effective optimization procedure based on a type of augmented Lagrange multipliers (ALM) method.