Machine learning has been heavily researched and widely used in many disciplines.
However, achieving high accuracy requires a large amount of data that is sometimes …

With the recent renaissance of deep convolutional neural networks (CNNs), encouraging
breakthroughs have been achieved on the supervised recognition tasks, where each class …

Facial attribute editing aims to manipulate single or multiple attributes on a given face
image, ie, to generate a new face image with desired attributes while preserving other …

We present a multi-purpose algorithm for simultaneous face detection, face alignment, pose
estimation, gender recognition, smile detection, age estimation and face recognition using a …

Face attribute estimation has many potential applications in video surveillance, face
retrieval, and social media. While a number of methods have been proposed for face …

Face attributes are interesting due to their detailed description of human faces. Unlike prior
researches working on attribute prediction, we address an inverse and more challenging …

We introduce several techniques for sampling and visualizing the latent spaces of
generative models. Replacing linear interpolation with spherical linear interpolation …

Attribute recognition, particularly facial, extracts many labels for each image. While some
multi-task vision problems can be decomposed into separate tasks and stages, eg, training …

Attributes, or mid-level semantic features, have gained popularity in the past few years in
domains ranging from activity recognition to face verification. Improving the accuracy of …

We demonstrate an approach to face attribute detection that retains or improves attribute
detection accuracy across gender and race subgroups by learning demographic information …