activity
20132018
most citedPatch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition

323 citations · 392 across the 9 of their papers we have counts for

collaborators
Showing cs.CVShow all

7 papers · 1 filter

cs.CV2018★ 2 cited

Convex Class Model on Symmetric Positive Definite Manifolds

Kun Zhao, Arnold Wiliem, Shaokang Chen +1

The effectiveness of Symmetric Positive Definite (SPD) manifold features has been proven in various computer vision tasks. However, due to the non-Euclidean geometry of these featu…

cs.CV2017

Using LIP to Gloss Over Faces in Single-Stage Face Detection Networks

Siqi Yang, Arnold Wiliem, Shaokang Chen +1

This work shows that it is possible to fool/attack recent state-of-the-art face detectors which are based on the single-stage networks. Successfully attacking face detectors could…

cs.CV2016

What is the Best Way for Extracting Meaningful Attributes from Pictures?

Liangchen Liu, Arnold Wiliem, Shaokang Chen +1

Automatic attribute discovery methods have gained in popularity to extract sets of visual attributes from images or videos for various tasks. Despite their good performance in some…

cs.CV2016★ 1 cited

Automatic and Quantitative evaluation of attribute discovery methods

Liangchen Liu, Arnold Wiliem, Shaokang Chen +1

Many automatic attribute discovery methods have been developed to extract a set of visual attributes from images for various tasks. However, despite good performance in some image…

cs.CV2014★ 4 cited

Matching Image Sets via Adaptive Multi Convex Hull

Shaokang Chen, Arnold Wiliem, Conrad Sanderson +1

Traditional nearest points methods use all the samples in an image set to construct a single convex or affine hull model for classification. However, strong artificial features and…

cs.CV2013★ 323 cited

Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition

Yongkang Wong, Shaokang Chen, Sandra Mau +2

In video based face recognition, face images are typically captured over multiple frames in uncontrolled conditions, where head pose, illumination, shadowing, motion blur and focus…