Human pose estimation refers to the estimation of the location of body parts and how they
are connected in an image. Human pose estimation from monocular images has wide …

In this work, we propose a novel and efficient method for articulated human pose estimation
in videos using a convolutional network architecture, which incorporates both color and …

We present a novel approach to efficiently learn a label tree for large scale classification with
many classes. The key contribution of the approach is a technique to simultaneously …

We present a method that can dramatically accelerate object detection with part based
models. The method is based on the observation that the cost of detection is likely …

We address the problem of articulated human pose estimation in videos using an ensemble
of tractable models with rich appearance, shape, contour and motion cues. In previous …

In this paper, we present a method for estimating articulated human poses in videos. We
cast this as an optimization problem defined on body parts with spatio-temporal links …

Our goal is to detect humans and estimate their 2D pose in single images. In particular,
handling cases of partial visibility where some limbs may be occluded or one person is …

Structured prediction tasks pose a fundamental trade-off between the need for model
complexity to increase predictive power and the limited computational resources for …

Human pose analysis has garnered significant attention within both the research community
and practical applications, owing to its expanding array of uses, including gaming, video …

This paper introduces a two-stage approach to semantic image segmentation. In the first
stage a probabilistic model generates a set of diverse plausible segmentations. In the …