SOTAVerified

VoxelKeypointFusion: Generalizable Multi-View Multi-Person Pose Estimation

2024-10-24Code Available0· sign in to hype

Daniel Bermuth, Alexander Poeppel, Wolfgang Reif

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

In the rapidly evolving field of computer vision, the task of accurately estimating the poses of multiple individuals from various viewpoints presents a formidable challenge, especially if the estimations should be reliable as well. This work presents an extensive evaluation of the generalization capabilities of multi-view multi-person pose estimators to unseen datasets and presents a new algorithm with strong performance in this task. It also studies the improvements by additionally using depth information. Since the new approach can not only generalize well to unseen datasets, but also to different keypoints, the first multi-view multi-person whole-body estimator is presented. To support further research on those topics, all of the work is publicly accessible.

Tasks

Benchmark Results

DatasetModelMetricClaimedVerifiedStatus
Human3.6MVoxelKeypointFusion (transfer)Average MPJPE (mm)64.3Unverified

Reproductions