Despite the large volume of face recognition datasets, there is a significant portion of
subjects, of which the samples are insufficient and thus under-represented. Ignoring such …

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 …

We present recursive cascaded networks, a general architecture that enables learning deep
cascades, for deformable image registration. The proposed architecture is simple in design …

Existing human pose estimation approaches often only consider how to improve the model
generalisation performance, but putting aside the significant efficiency problem. This leads …

Recent advances in facial landmark detection achieve success by learning discriminative
features from rich deformation of face shapes and poses. Besides the variance of faces …

Compositional models represent patterns with hierarchies of meaningful parts and subparts.
Their ability to characterize high-order relationships among body parts helps resolve low …

Despite recent advances in face recognition using deep learning, severe accuracy drops are
observed for large pose variations in unconstrained environments. Learning pose-invariant …

Recognizing wild faces is extremely hard as they appear with all kinds of variations.
Traditional methods either train with specifically annotated variation data from target …

Regression based facial landmark detection methods usually learns a series of regression
functions to update the landmark positions from an initial estimation. Most of existing …

In this paper, we tackle the problem of human pose estimation from still images, which is a
very active topic, specially due to its several applications, from image annotation to human …