Traditional architectures for solving computer vision problems and the degree of success
they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep …

Face alignment is a crucial component in most face analysis systems. It focuses on
identifying the location of several keypoints of the human faces in images or videos …

Automatic face alignment is a fundamental step in facial image analysis. However, this
problem continues to be challenging due to the large variability of expression, illumination …

This work proposes Multi-task Meta Learning (MTML), integrating two learning paradigms
Multi-Task Learning (MTL) and meta learning, to bring together the best of both worlds. In …

Person reidentification involves recognizing a person across nonoverlapping camera views,
with different pose, illumination, and camera characteristics. We propose to tackle this …

In this paper, we propose a new cascaded deep auto-encoder networks (CDAN) approach
for face alignment. Our framework consists of a global exemplar-based deep auto-encoder …

In this paper, we develop a spatio-temporal cascade shape regression (STCSR) model for
robust facial shape tracking. It is different from previous works in three aspects. Firstly, a …

Traditional architectures for solving computer vision problems and the degree of success
they enjoyed have been heavily reliant on hand-crafted features. However, of late, deep …

Deep learning shows superiority in learning feature representations that offer promising
performance in various application domains. Recent advances have shown that privacy …

Eyeglass reflection removal is of great importance to the portrait image processing.
However, it remains a challenge to eliminate the reflections on the glass and restore the …