We characterize the problem of pose estimation for rigid objects in terms of determining
viewpoint to explain coarse pose and keypoint prediction to capture the finer details. We …

For applications in navigation and robotics, estimating the 3D pose of objects is as important
as detection. Many approaches to pose estimation rely on detecting or tracking parts or …

Object recognition and viewpoint estimation lie at the heart of visual understanding. Recent
studies have suggested that convolutional neural networks (CNNs) fail to generalize to out …

Deep Convolutional Neural Networks (DCNN) have been proven to be effective for various
computer vision problems. In this work, we demonstrate its effectiveness on a continuous …

The six-dimensional (6-D) pose estimation of smooth metal parts is a common and important
task in intelligent manufacturing. Computer-aided design (CAD)-based monocular vision …

We address the problem of fully automatic object localization and reconstruction from a
single image. This is both a very challenging and very important problem which has, until …

Despite growing research interest, emotion understanding for user-generated videos
remains a challenging problem. Major obstacles include the diversity and complexity of …

Body orientation estimation provides crucial visual cues in many applications, including
robotics and autonomous driving. It is particularly desirable when 3-D pose estimation is …

Pedestrian detection is an important task for human-robot interaction and autonomous
driving applications. Most previous pedestrian detection methods rely on data collected from …

We argue for the importance of the interaction between recognition, reconstruction and re-
organization, and propose that as a unifying framework for computer vision. In this view …