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 …

Human pose estimation localizes body keypoints to accurately recognizing the postures of
individuals given an image. This step is a crucial prerequisite to multiple tasks of computer …

Abstract The problem of Multiple Object Tracking (MOT) consists in following the trajectory of
different objects in a sequence, usually a video. In recent years, with the rise of Deep …

Standardized benchmarks have been crucial in pushing the performance of computer vision
algorithms, especially since the advent of deep learning. Although leaderboards should not …

Humans are able to form a complex mental model of the environment they move in. This
mental model captures geometric and semantic aspects of the scene, describes the …

In this work, we propose a method that combines a single hand-held camera and a set of
Inertial Measurement Units (IMUs) attached at the body limbs to estimate accurate 3D poses …

We present an approach to efficiently detect the 2D pose of multiple people in an image. The
approach uses a nonparametric representation, which we refer to as Part Affinity Fields …

This paper addresses the challenge of 3D human pose estimation from a single color image.
Despite the general success of the end-to-end learning paradigm, top performing …

Pose Machines provide a sequential prediction framework for learning rich implicit spatial
models. In this work we show a systematic design for how convolutional networks can be …

Tracking objects in soccer videos is extremely important to gather both player and team
statistics, whether it is to estimate the total distance run, the ball possession or the team …