Head pose estimation suffers from several problems, including low pose tolerance under
different disturbances and ambiguity arising from common head pose representation. In this …

This paper proposes a method for head pose estimation from a single image. Previous
methods often predict head poses through landmark or depth estimation and would require …

Head pose estimation (HPE) is an indispensable upstream task in the fields of human-
machine interaction, self-driving, and attention detection. However, practical head pose …

Learning articulated object pose is inherently difficult because the pose is high dimensional
but has many structural constraints. Most existing work do not model such constraints and …

Many successful models for scene or object recognition transform low-level descriptors
(such as Gabor filter responses, or SIFT descriptors) into richer representations of …

Head pose estimation (HPE) has been widely used in the fields of human machine
interaction, self-driving, and attention estimation. However, existing methods cannot deal …

Head pose estimation has attracted immense research interest recently, as its inherent
information significantly improves the performance of face-related applications such as face …

Fast and accurate upper-body and head pose estimation is a key task for automatic
monitoring of driver attention, a challenging context characterized by severe illumination …

In this paper, we propose head pose estimation using deep neural networks and 3D point
cloud. Unlike existing methods that either take 2D RGB image or 2D depth image as input …

Facial analysis in videos, including head pose estimation and facial landmark localization, is
key for many applications such as facial animation capture, human activity recognition, and …