TY - GEN
T1 - SSD-6D
T2 - 16th IEEE International Conference on Computer Vision, ICCV 2017
AU - Kehl, Wadim
AU - Manhardt, Fabian
AU - Tombari, Federico
AU - Ilic, Slobodan
AU - Navab, Nassir
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/12/22
Y1 - 2017/12/22
N2 - We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover the full 6D pose space and train on synthetic model data only. Our approach competes or surpasses current state-of-the-art methods that leverage RGBD data on multiple challenging datasets. Furthermore, our method produces these results at around 10Hz, which is many times faster than the related methods. For the sake of reproducibility, we make our trained networks and detection code publicly available.
AB - We present a novel method for detecting 3D model instances and estimating their 6D poses from RGB data in a single shot. To this end, we extend the popular SSD paradigm to cover the full 6D pose space and train on synthetic model data only. Our approach competes or surpasses current state-of-the-art methods that leverage RGBD data on multiple challenging datasets. Furthermore, our method produces these results at around 10Hz, which is many times faster than the related methods. For the sake of reproducibility, we make our trained networks and detection code publicly available.
UR - https://www.scopus.com/pages/publications/85041907567
U2 - 10.1109/ICCV.2017.169
DO - 10.1109/ICCV.2017.169
M3 - Conference contribution
AN - SCOPUS:85041907567
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 1530
EP - 1538
BT - Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 22 October 2017 through 29 October 2017
ER -