Core Concepts
EgoTAP introduces a novel method for accurate stereo egocentric 3D pose estimation, outperforming existing approaches.
Abstract
EgoTAP addresses challenges in egocentric pose estimation by utilizing a Grid ViT Encoder and a Propagation Network.
The Grid ViT Encoder summarizes joint heatmaps effectively using self-attention.
The Propagation Network estimates 3D pose by leveraging skeletal information for better joint position estimation.
EgoTAP significantly reduces error in pose estimation metrics, showcasing its superiority.
The method is evaluated on UnrealEgo and EgoCap datasets, demonstrating substantial improvements over state-of-the-art methods.
Ablation studies highlight the effectiveness of each network component, emphasizing the importance of the Propagation Network.
Stats
우리의 방법은 MPJPE 메트릭에서 23.9%의 오류 감소를 보여줍니다.
Quotes
"Our method significantly outperforms the previous state-of-the-art qualitatively and quantitatively."