Papers Face Clustering
“Face Clustering” 태그가 달린 논문 63편 · 필터 해제
Enhancing Noise Resilience in Face Clustering via Sparse Differential Transformer
The method used to measure relationships between face embeddings plays a crucial role in determining the performance of face clustering. Existing methods employ the Jaccard similarity coefficient instead of the cosine di…
Face ClusteringFace Clustering via Early Stopping and Edge Recall
Large-scale face clustering has achieved significant progress, with many efforts dedicated to learning to cluster large-scale faces with supervised-learning. However, complex model design and tedious clustering processes…
ClusteringFace ClusteringVideoClusterNet: Self-Supervised and Adaptive Face Clustering For Videos
With the rise of digital media content production, the need for analyzing movies and TV series episodes to locate the main cast of characters precisely is gaining importance.Specifically, Video Face Clustering aims to gr…
ClusteringFace ClusteringFace IdentificationImproved Face Representation via Joint Label Classification and Supervised Contrastive Clustering
Face clustering tasks can learn hierarchical semantic information from large-scale data, which has the potential to help facilitate face recognition. However, there are few works on this problem. This paper explores it b…
ClusteringFace ClusteringFace RecognitionLearn to Cluster Faces with Better Subgraphs
Face clustering can provide pseudo-labels to the massive unlabeled face data and improve the performance of different face recognition models. The existing clustering methods generally aggregate the features within subgr…
ClusteringFace ClusteringFace RecognitionLocal Connectivity-Based Density Estimation for Face Clustering
Recent graph-based face clustering methods predict the connectivity of enormous edges, including false positive edges that link nodes with different classes. However, those false positive edges, which connect negativ…
ClusteringConnectivity EstimationDensity EstimationFace Clustering+1Face Clustering via Graph Convolutional Networks with Confidence Edges
Face clustering is a method for unlabeled image annotation and has attracted increasing attention. Existing methods have made significant breakthroughs by introducing Graph Convolutional Networks (GCNs) on the affini…
ClusteringFace ClusteringCLIP-Cluster: CLIP-Guided Attribute Hallucination for Face Clustering
One of the most important yet rarely studied challenges for supervised face clustering is the large intra-class variance caused by different face attributes such as age, pose, and expression. Images of the same ident…
AttributeClusteringFace ClusteringHallucinationRobust Graph Structure Learning via Multiple Statistical Tests
Graph structure learning aims to learn connectivity in a graph from data. It is particularly important for many computer vision related tasks since no explicit graph structure is available for images for most cases. A na…
Face ClusteringGraph structure learningOn the Robustness of Deep Clustering Models: Adversarial Attacks and Defenses
Clustering models constitute a class of unsupervised machine learning methods which are used in a number of application pipelines, and play a vital role in modern data science. With recent advancements in deep learning -…
ClusteringDeep ClusteringFace ClusteringOn Mitigating Hard Clusters for Face Clustering
Face clustering is a promising way to scale up face recognition systems using large-scale unlabeled face images. It remains challenging to identify small or sparse face image clusters that we call hard clusters, which is…
ClusteringFace ClusteringFace RecognitionLearn to Cluster Faces via Pairwise Classification
Face clustering plays an essential role in exploiting massive unlabeled face data. Recently, graph-based face clustering methods are getting popular for their satisfying performances. However, they usually suffer from ex…
ClassificationClusteringFace ClusteringCharacter-focused Video Thumbnail Retrieval
We explore retrieving character-focused video frames as candidates for being video thumbnails. To evaluate each frame of the video based on the character(s) present in it, characters (faces) are evaluated in two aspects:…
Face ClusteringRetrievalAnalysis of Sparse Subspace Clustering: Experiments and Random Projection
Clustering can be defined as the process of assembling objects into a number of groups whose elements are similar to each other in some manner. As a technique that is used in many domains, such as face clustering, plant …
ClusteringDocument ClassificationFace ClusteringImage Segmentation+1Using Active Speaker Faces for Diarization in TV shows
Speaker diarization is one of the critical components of computational media intelligence as it enables a character-level analysis of story portrayals and media content understanding. Automated audio-based speaker diariz…
Face ClusteringFace Detectionspeaker-diarizationSpeaker DiarizationSelf-supervised Video-centralised Transformer for Video Face Clustering
This paper presents a novel method for face clustering in videos using a video-centralised transformer. Previous works often employed contrastive learning to learn frame-level representation and used average pooling to a…
ClusteringContrastive LearningFace ClusteringFaceMap: Towards Unsupervised Face Clustering via Map Equation
Face clustering is an essential task in computer vision due to the explosion of related applications such as augmented reality or photo album management. The main challenge of this task lies in the imperfectness of simil…
ClusteringCommunity DetectionFace ClusteringManagement+1Ada-NETS: Face Clustering via Adaptive Neighbour Discovery in the Structure Space
Face clustering has attracted rising research interest recently to take advantage of massive amounts of face images on the web. State-of-the-art performance has been achieved by Graph Convolutional Networks (GCN) due to …
ClusteringFace ClusteringDensity-Based Clustering with Kernel Diffusion
Finding a suitable density function is essential for density-based clustering algorithms such as DBSCAN and DPC. A naive density corresponding to the indicator function of a unit $d$-dimensional Euclidean ball is commonl…
ClusteringFace ClusteringA Linkage-based Doubly Imbalanced Graph Learning Framework for Face Clustering
In recent years, benefiting from the expressive power of Graph Convolutional Networks (GCNs), significant breakthroughs have been made in face clustering area. However, rare attention has been paid to GCN-based clusterin…
ClusteringFace ClusteringGraph Learningimage-classification+1