AI RESEARCH
Auto-Annotation with Expert-Crafted Guidelines: A Study through 3D LiDAR Detection Benchmark
arXiv CS.CV
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ArXi:2506.02914v2 Announce Type: replace Data annotation is crucial for developing machine learning solutions. The current paradigm is to hire ordinary human annotators to annotate data instructed by expert-crafted guidelines. As this paradigm is laborious, tedious, and costly, we are motivated to explore auto-annotation with expert-crafted guidelines. To this end, we first develop a ing benchmark AutoExpert by repurposing the established nuScenes dataset, which has been widely used in autonomous driving research and provides authentic expert-crafted guidelines.