PACE: Pose Annotations in Cluttered Environments

Published in ECCV, 2024

Pose estimation is vital for tracking and manipulating objects in images or videos. Existing datasets lack a focus on cluttered scenes with occlusions, hindering real-world application development. To address this, we introduce PACE (Pose Annotations in Cluttered Environments), a large-scale benchmark for evaluating pose estimation methods in cluttered scenarios. PACE includes 54,945 frames with 257,673 annotations across 300 videos, featuring 576 objects from 44 categories. An innovative annotation system with a 3-camera setup was developed for efficient real-world data annotation.