In this paper, we propose a novel regional multi-person pose estimation (RMPE) framework to facilitate pose estimation in the presence of inaccurate human bounding boxes.
Ranked #1 on
Keypoint Detection
on MPII Multi-Person
2D HUMAN POSE ESTIMATION HUMAN DETECTION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION
This paper addresses the problem of estimating and tracking human body keypoints in complex, multi-person video.
Ranked #5 on
Pose Tracking
on PoseTrack2017
(using extra training data)
HUMAN DETECTION MULTI-OBJECT TRACKING POSE ESTIMATION POSE TRACKING VIDEO UNDERSTANDING
Our second contribution is to provide the first fully automatic Spatial PerceptIon eNgine(SPIN) to build a DSG from visual-inertial data.
3D RECONSTRUCTION HUMAN DETECTION ROBOT TASK PLANNING SIMULTANEOUS LOCALIZATION AND MAPPING
The 1st Tiny Object Detection (TOD) Challenge aims to encourage research in developing novel and accurate methods for tiny object detection in images which have wide views, with a current focus on tiny person detection.
In this paper, we introduce a new benchmark, referred to as TinyPerson, opening up a promising directionfor tiny object detection in a long distance and with mas-sive backgrounds.
In this paper, we present MultiPoseNet, a novel bottom-up multi-person pose estimation architecture that combines a multi-task model with a novel assignment method.
Ranked #5 on
Multi-Person Pose Estimation
on COCO
4 HUMAN DETECTION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION
The rapid improvement of language models has raised the specter of abuse of text generation systems.
First, we leverage person-scene relations and propose a Global CNN model trained to predict positions and scales of heads directly from the full image.
This paper proposes a new Generative Partition Network (GPN) to address the challenging multi-person pose estimation problem.
Ranked #1 on
Multi-Person Pose Estimation
on WAF
(AP metric)
HUMAN DETECTION KEYPOINT DETECTION MULTI-PERSON POSE ESTIMATION
Some of these approaches have also shown that these attacks are feasible in the real-world, i. e. by modifying an object and filming it with a video camera.