Recent years have witnessed enormous progress in AI-related fields such as computer
vision, machine learning, and autonomous vehicles. As with any rapidly growing field, it …

Estimating the pose of a human in 3D given an image or a video has recently received
significant attention from the scientific community. The main reasons for this trend are the …

Despite progress in perceptual tasks such as image classification, computers still perform
poorly on cognitive tasks such as image description and question answering. Cognition is …

In this paper, we propose to incorporate convolutional neural networks with a multi-context
attention mechanism into an end-to-end framework for human pose estimation. We adopt …

We present an approach to capture the 3D structure and motion of a group of people
engaged in a social interaction. The core challenges in capturing social interactions are:(1) …

In this paper, we propose deformable deep convolutional neural networks for generic object
detection. This new deep learning object detection diagram has innovations in multiple …

Human faces captured in real-world conditions present large variations in shape and
occlusions due to differences in pose, expression, use of accessories such as sunglasses …

In this paper, we tackle the problem of human pose estimation from still images, which is a
very active topic, specially due to its several applications, from image annotation to human …

In this paper, we propose deformable deep convolutional neural networks for generic object
detection. This new deep learning object detection framework has innovations in multiple …

Studying free-standing conversational groups (FCGs) in unstructured social settings (eg,
cocktail party) is gratifying due to the wealth of information available at the group (mining …