Existing methods of 3D dthus limiting the scope of their practical applications. In this paper,
we propose a novel regression framework which makes a balance among speed, accuracy …

The task of facial landmark extraction is fundamental in several applications which involve
facial analysis, such as facial expression analysis, identity and face recognition, facial …

Abstract Constrained Local Models (CLMs) are a well-established family of methods for
facial landmark detection. CE-CLM, the newest member of CLMs, brings CLMs back to state …

Recently proposed robust 3D face alignment methods establish either dense or sparse
correspondence between a 3D face model and a 2D facial image. The use of these methods …

Dense facial landmark detection is one of the key elements of face processing pipeline. It is
used in virtual face reenactment, emotion recognition, driver status tracking, etc. Early …

Computer Vision (CV) classifiers which distinguish and detect nonverbal social human
behavior and mental state can aid digital diagnostics and therapeutics for psychiatry and the …

In this paper, we propose a novel machine learning architecture for facial reenactment. In
particular, contrary to the model-based approaches or recent frame-based methods that use …

In this article, we present the Menpo 2D and Menpo 3D benchmarks, two new datasets for
multi-pose 2D and 3D facial landmark localisation and tracking. In contrast to the previous …

We introduce DOPE, the first method to detect and estimate whole-body 3D human poses,
including bodies, hands and faces, in the wild. Achieving this level of details is key for a …

Facial landmark localisation in images captured in-the-wild is an important and challenging
problem. The current state-of-the-art revolves around certain kinds of Deep Convolutional …