In this technical report, we present the 1st place solution for the 2023
Waymo Open Dataset Pose Estimation challenge. Due to the difficulty of
acquiring large-scale 3D human keypoint annotation, previous methods have
commonly relied on 2D image features and 2D sequential annotations for 3D human
pose estimation. In contrast, our proposed method, named LPFormer, uses only
LiDAR as its input along with its corresponding 3D annotations. LPFormer
consists of two stages: the first stage detects the human bounding box and
extracts multi-level feature representations, while the second stage employs a
transformer-based network to regress the human keypoints using these features.
Experimental results on the Waymo Open Dataset demonstrate the top performance,
and improvements even compared to previous multi-modal solutions.Comment: Technical report of the top solution for the Waymo Open Dataset
Challenges 2023 - Pose Estimation. CVPR 2023 Workshop on Autonomous Drivin