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
Density-Based Clustering with Kernel Diffusion
Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC.
Face, Body, Voice: Video Person-Clustering with Multiple Modalities
In this paper we make contributions to address both these deficiencies: first, we introduce a Multi-Modal High-Precision Clustering algorithm for person-clustering in videos using cues from several modalities (face, body, and voice).
Learning to Cluster Faces via Transformer
In this paper, we repurpose the well-known Transformer and introduce a Face Transformer for supervised face clustering.
Efficient Large-Scale Face Clustering Using an Online Mixture of Gaussians
In this work, we address the problem of large-scale online face clustering: given a continuous stream of unknown faces, create a database grouping the incoming faces by their identity.
Orthogonal Subspace Decomposition: A New Perspective of Learning Discriminative Features for Face Clustering
Learning discriminative node features is the key to further improve the performance of graph-based face clustering.
A Clustering-Based Method for Automatic Educational Video Recommendation Using Deep Face-Features of Lecturers
Discovering and accessing specific content within educational video bases is a challenging task, mainly because of the abundance of video content and its diversity.
Robust Character Labeling in Movie Videos: Data Resources and Self-supervised Feature Adaptation
Our work in this paper focuses on two key aspects of this problem: the lack of domain-specific training or benchmark datasets, and adapting face embeddings learned on web images to long-form content, specifically movies.
Improving Face Recognition by Clustering Unlabeled Faces in the Wild
While deep face recognition has benefited significantly from large-scale labeled data, current research is focused on leveraging unlabeled data to further boost performance, reducing the cost of human annotation.
Density-Aware Feature Embedding for Face Clustering
In this paper, we propose a Density-Aware Feature Embedding Network (DA-Net) for the task of face clustering, which utilizes both local and non-local information, to learn a robust feature embedding.
Is an Affine Constraint Needed for Affine Subspace Clustering?
Specifically, our analysis provides conditions that guarantee the correctness of affine subspace clustering methods both with and without the affine constraint, and shows that these conditions are satisfied for high-dimensional data.
