Human Detection
82 papers with code • 0 benchmarks • 13 datasets
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Libraries
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Most implemented papers
Generative Partition Networks for Multi-Person Pose Estimation
This paper proposes a new Generative Partition Network (GPN) to address the challenging multi-person pose estimation problem.
Vision-Based Fallen Person Detection for the Elderly
Furthermore, our system consists of a reasoning module which formulates a number of measures to reason whether a person is fallen.
Holistic, Instance-Level Human Parsing
We address this problem by segmenting the parts of objects at an instance-level, such that each pixel in the image is assigned a part label, as well as the identity of the object it belongs to.
An Order Preserving Bilinear Model for Person Detection in Multi-Modal Data
We propose a new order preserving bilinear framework that exploits low-resolution video for person detection in a multi-modal setting using deep neural networks.
Detect-and-Track: Efficient Pose Estimation in Videos
This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video.
Survey on Emotional Body Gesture Recognition
Automatic emotion recognition has become a trending research topic in the past decade.
Deep Person Detection in 2D Range Data
Detecting humans is a key skill for mobile robots and intelligent vehicles in a large variety of applications.
CrowdHuman: A Benchmark for Detecting Human in a Crowd
There are a total of $470K$ human instances from the train and validation subsets, and $~22. 6$ persons per image, with various kinds of occlusions in the dataset.
MVOR: A Multi-view RGB-D Operating Room Dataset for 2D and 3D Human Pose Estimation
In this paper, we present the dataset, its annotations, as well as baseline results from several recent person detection and 2D/3D pose estimation methods.
A Mobile Robot Generating Video Summaries of Seniors' Indoor Activities
We develop a system which generates summaries from seniors' indoor-activity videos captured by a social robot to help remote family members know their seniors' daily activities at home.