Abstract The goal of Facial Kinship Verification (FKV) is to automatically determine whether
two individuals have a kin relationship or not from their given facial images or videos. It is an …

Machine learning methods have achieved good performance and been widely applied in
various real-world applications. They can learn the model adaptively and be better fit for …

Kinship verification is an emerging task in computer vision which aims at finding out whether
there is a kin relation between given identities through their facial images. Applications of …

Most existing automatic kinship verification methods focus on learning the optimal distance
metrics between family members. However, learning facial features and kinship features …

Kinship recognition is a prominent research aiming to find if kinship relation exists between
two different individuals. In general, child closely resembles his/her parents more than …

With the development of deep learning techniques, fusion of deep features has
demonstrated the powerful capability to improve recognition performance. However, most …

One of the visually noticeable compression artifacts in block-based image/video
compression platforms is called blocking artifact. Several post-processing methods were …

Deep metric learning (DML) has achieved state-of-the-art results in several deep learning
applications. However, this type of deep learning models has not been tested on the …

Scale variation because of perspective distortion is still a challenge for crowd analysis. To
address this problem, an atrous convolutions spatial pyramid network (ACSPNet) is …

This paper presents a new Tensor Cross-view Quadratic Discriminant Analysis (TXQDA)
method based on the XQDA method for kinship verification in the wild. Many researchers …