Mar 3, 2019 · In this paper, we address video face clustering using unsupervised methods. Our emphasis is on distilling the essential information, identity, ...

Oct 17, 2019 · In this paper, we propose unsupervised methods for feature refinement with application to video face clustering. Our emphasis is on distilling ...

SSiam selects hard pairs: farthest positives and closest negatives using a ranked list based on Euclidean distance for learning similarity and dissimilarity.

Oct 13, 2019 · In this paper, we propose unsupervised methods for feature refinement with application to video face clustering.

This paper proposes a self-supervised Siamese network that can be trained without the need for video/track based supervision, and thus can also be applied ...

We present a fully self-supervised video face clustering framework that efficiently auto-adapts to specific variations observed in set of faces in a given video ...

In this paper, we aim to learn discriminative representa- tion for facial action unit (AU) detection from large amount of videos without manual annotations.

Video Face Clustering with Self-Supervised Representation Learning ; Author: V. Sharma, M. Tapaswi, M. S. Sarfraz, R. Stiefelhagen ; Source: IEEE Transactions on ...

Jul 16, 2024 · Overall, our proposed method VideoClusterNet can be divided into two main stages. The first stage involves a fully self-supervised learning (SSL) ...

This paper proposes a self-supervised Siamese network that can be trained without the need for video/track based supervision, that can also be applied to ...