In real-world face detection, large visual variations, such as those due to pose, expression,
and lighting, demand an advanced discriminative model to accurately differentiate faces from …

Although weight and activation quantization is an effective approach for Deep Neural Network
(DNN) compression and has a lot of potentials to increase inference speed leveraging bit-…

We present variational generative adversarial networks, a general learning framework that
combines a variational auto-encoder with a generative adversarial network, for synthesizing …

In this paper, we explore methods for learning local image descriptors from training data.
We describe a set of building blocks for constructing descriptors which can be combined …

In this paper, we study the problem of image-text matching. Inferring the latent semantic
alignment between objects or other salient stuff (eg snow, sky, lawn) and the corresponding …

Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of
leveraging traditional low-level or handcrafted image priors as the restoration constraints, eg, …

To address the non-stationary property of aging patterns, age estimation can be cast as an
ordinal regression problem. However, the processes of extracting features and learning a …

In 2007, Labeled Faces in the Wild was released in an effort to spur research in face recognition,
specifically for the problem of face verification with unconstrained images. Since that …

We propose StyleBank, which is composed of multiple convolution filter banks and each filter
bank explicitly represents one style, for neural image style transfer. To transfer an image to …

We propose a new technique for visual attribute transfer across images that may have very
different appearance but have perceptually similar semantic structure. By visual attribute …