This paper proposes to perform online clustering by conducting twin contrastive learning
(TCL) at the instance and cluster level. Specifically, we find that when the data is projected …

Graph convolution networks (GCN) have recently become popular for image clustering.
However, existing GCN-based image clustering techniques focus on learning image …

Recent years witnessed the breakthrough of face recognition with deep convolutional neural
networks. Dozens of papers in the field of FR are published every year. Some of them were …

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 …

Video object detection is a fundamental and important task in computer vision. One mainstay
solution for this task is to aggregate features from different frames to enhance the detection …

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 …

In various verification systems, Restricted Boltzmann Machines (RBMs) have demonstrated
their efficacy in both front-end and back-end processes. In this work, we propose the use of …

Unsupervised vision clustering, a cornerstone in computer vision, has been studied for
decades, yielding signif-icant outcomes across numerous vision tasks. However, these …

Although quantum machine learning has been introduced for a while, its applications in
computer vision are still limited. This paper, therefore, revisits the quantum visual encoding …

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 …