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This technical report describes our first-place solution to the poseestimation challenge at ECCV 2022 Visual Perception for Navigation in HumanEnvironments Workshop. In this challenge, we aim to estimate human poses fromin-the-wild stitched panoramic images. Our method is built based on FasterR-CNN for human detection, and HRNet for human pose estimation. We describetechnical details for the JRDB-Pose dataset, together with some experimentalresults. In the competition, we achieved 0.303 $\text{OSPA}_{\text{IOU}}$ and64.047\% $\text{AP}_{\text{0.5}}$ on the test set of JRDB-Pose.

An Improved Baseline Framework for Pose Estimation Challenge at ECCV 2022 Visual Perception for Navigation in Human Environments Workshop