End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

Original language	English
Title of host publication	2021 IEEE International Conference on Robotics and Automation (ICRA)
Pages	13452 - 13458
Number of pages	7
Publication status	Published - 2021
Event	2021 IEEE International Conference on Robotics and Automation : ICRA 2021 - Xi'an, Hybrider Event, China Duration: 31 May 2021 → 4 Jun 2021

Conference	2021 IEEE International Conference on Robotics and Automation
Abbreviated title	ICRA 2021
Country/Territory	China
City	Xi'an, Hybrider Event
Period	31/05/21 → 4/06/21

End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB
Stefan Ainetter (Speaker)
3 Jun 2021
Activity: Talk or presentation › Talk at conference or symposium › Science to science

Cite this

@inproceedings{1a103f5e5beb4de19b5ae1a883b60a02,

title = "End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB",

author = "Stefan Ainetter and Friedrich Fraundorfer",

year = "2021",

language = "English",

pages = "13452 -- 13458",

booktitle = "2021 IEEE International Conference on Robotics and Automation (ICRA)",

note = "2021 IEEE International Conference on Robotics and Automation : ICRA 2021, ICRA 2021 ; Conference date: 31-05-2021 Through 04-06-2021",

}

TY - GEN

T1 - End-to-end Trainable Deep Neural Network for Robotic Grasp Detection and Semantic Segmentation from RGB

AU - Ainetter, Stefan

AU - Fraundorfer, Friedrich

PY - 2021

Y1 - 2021

M3 - Conference paper

SP - 13452

EP - 13458

BT - 2021 IEEE International Conference on Robotics and Automation (ICRA)

T2 - 2021 IEEE International Conference on Robotics and Automation

Y2 - 31 May 2021 through 4 June 2021

ER -