The elements of end-to-end deep face recognition: A survey of recent advances
Face recognition (FR) is one of the most popular and long-standing topics in computer
vision. With the recent development of deep learning techniques and large-scale datasets …
vision. With the recent development of deep learning techniques and large-scale datasets …
Eqface: A simple explicit quality network for face recognition
R Liu, W Tan - Proceedings of the IEEE/CVF Conference on …, 2021 - openaccess.thecvf.com
As the deep learning makes big progresses in still-image face recognition, unconstrained
video face recognition is still a challenging task due to low quality face images caused by …
video face recognition is still a challenging task due to low quality face images caused by …
Discriminability distillation in group representation learning
Learning group representation is a commonly concerned issue in tasks where the basic unit
is a group, set, or sequence. Previously, the research community tries to tackle it by …
is a group, set, or sequence. Previously, the research community tries to tackle it by …
Deep discriminative feature models (DDFMs) for set based face recognition and distance metric learning
This article introduces two methods that find compact deep feature models for approximating
images in set based face recognition problems. The proposed method treats each image set …
images in set based face recognition problems. The proposed method treats each image set …
Two-directional two-dimensional fractional-order embedding canonical correlation analysis for multi-view dimensionality reduction and set-based video recognition
Set-based video recognition is an important application in practice, and many specialized
approaches have been proposed. However, most of these methods either only use one kind …
approaches have been proposed. However, most of these methods either only use one kind …
Redundancy removing aggregation network with distance calibration for video face recognition
Attention-based techniques have been successfully used for rating image quality, and have
been widely employed for set-based face recognition. Nevertheless, for video face …
been widely employed for set-based face recognition. Nevertheless, for video face …
Face aggregation network for video face recognition
Typical approaches for video face recognition aggregate faces in a feature space to obtain a
single feature representing the entire video. Unlike most previous approaches, we …
single feature representing the entire video. Unlike most previous approaches, we …
VideoClusterNet: Self-supervised and Adaptive Face Clustering for Videos
D Walawalkar, P Garrido - European Conference on Computer Vision, 2025 - Springer
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 …
series episodes to locate the main cast of characters precisely is gaining importance …
Set-Based Face Recognition Beyond Disentanglement: Burstiness Suppression With Variance Vocabulary
Set-based face recognition (SFR) aims to recognize the face sets in the unconstrained
scenario, where the appearance of same identity may change dramatically with extreme …
scenario, where the appearance of same identity may change dramatically with extreme …
G-FAN: graph-based feature aggregation network for video face recognition
In this paper, we propose a graph-based feature aggregation network (G-FAN) for video face
recognition. Compared with the still image, video face recognition exhibits great challenges …
recognition. Compared with the still image, video face recognition exhibits great challenges …