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
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)
Our second contribution is to provide the first fully automatic Spatial PerceptIon eNgine(SPIN) to build a DSG from visual-inertial data.
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 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
The rapid improvement of language models has raised the specter of abuse of text generation systems.
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)
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.