Deep neural networks have become prevalent in human analysis, boosting the performance
of applications, such as biometric recognition, action recognition, as well as person re …

Abstract 3D face recognition (3DFR) has emerged as an effective means of characterizing
facial identity over the past several decades. Depending on the types of techniques used in …

High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …

We present a novel boundary-aware face alignment algorithm by utilising boundary lines as
the geometric structure of a human face to help facial landmark localisation. Unlike the …

We present a new loss function, namely Wing loss, for robust facial landmark localisation
with Convolutional Neural Networks (CNNs). We first compare and analyse different loss …

One of the major challenges in anatomical landmark detection, based on deep neural
networks, is the limited availability of medical imaging data for network learning. To address …

This paper investigates the task of 2D whole-body human pose estimation, which aims to
localize dense landmarks on the entire human body including body, feet, face, and hands …

The recent progress of CNN has dramatically improved face alignment performance.
However, few works have paid attention to the error-bias with respect to error distribution of …

The quality and size of training set have a great impact on the results of deep learning-
based face-related tasks. However, collecting and labeling adequate samples with high …

Deep convolutional neural networks have recently proven extremely effective for difficult
face recognition problems in uncontrolled settings. To train such networks, very large …