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Real-World Semantic Grasp Detection Based on Attention Mechanism
[article]
2022
arXiv
pre-print
Recognizing the category of the object and using the features of the object itself to predict grasp configuration is of great significance to improve the accuracy of the grasp detection model and expand its application. Researchers have been trying to combine these capabilities in an end-to-end network to grasping specific objects in a cluttered scene efficiently. In this paper, we propose an end-to-end semantic grasp detection model, which can accomplish both semantic recognition and grasp
arXiv:2111.10522v2
fatcat:5qpnsydrn5egvajlvedx7g2tmy