Spatial landmarks are crucial in describing histological features between samples or sites,
tracking regions of interest in microscopy, and registering tissue samples within a common …

Action Units (AUs) are geometrically-based atomic facial muscle movements known to
produce appearance changes at specific facial locations. Motivated by this observation we …

Gait recognition is an emerging biometric technology for identifying pedestrians based on
their unique walking patterns. In past gait recognition, global-based methods are inadequate …

Unsupervised landmarks discovery (ULD) for an object category is a challenging computer
vision problem. In pursuit of develo** a robust ULD framework we explore the potential of …

While GANs have shown success in realistic image generation, the idea of using GANs for
other tasks unrelated to synthesis is underexplored. Do GANs learn meaningful structural …

We develop techniques for refining representations for fine-grained classification and
segmentation tasks in a self-supervised manner. We find that fine-tuning methods based on …

Landmark detection is a fundamental task aiming at identifying specific landmarks that serve
as representations of distinct object features within an image. However, the present …

Holistic methods using CNNs and margin-based losses have dominated research on face
recognition. In this work, we depart from this setting in two ways:(a) we employ the Vision …

This paper addresses the problem of unsupervised discovery of object landmarks. We take a
different path compared to that of existing works, based on 2 novel perspectives:(1) Self …

Deep learning approaches have advanced state-of-the-art performance drastically in facial
landmark detection and head pose estimation. Recent work shows that meaningful …