Label Anything: An Interpretable, High-Fidelity and Prompt-Free Annotator

Fuente: arXiv

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Bibliographic Details
Main Authors:	Kou, Wei-Bin, Zhu, Guangxu, Ye, Rongguang, Wang, Shuai, Tang, Ming, Wu, Yik-Chung
Format:	Preprint
Published:	2025
Subjects:	Robotics Machine Learning
Online Access:	Acceder al recurso
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Internet

https://arxiv.org/abs/2502.02972