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FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose
  Estimation

FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation

18 September 2024
Thomas Pöllabauer
Ashwin Pramod
Volker Knauthe
Michael Wahl
ArXiv (abs)PDFHTML

Papers citing "FAST GDRNPP: Improving the Speed of State-of-the-Art 6D Object Pose Estimation"

14 / 14 papers shown
Title
Extending 6D Object Pose Estimators for Stereo Vision
Extending 6D Object Pose Estimators for Stereo Vision
Thomas Pollabauer
Jan Emrich
Volker Knauthe
Arjan Kuijper
MDE
48
4
0
08 Feb 2024
FasterViT: Fast Vision Transformers with Hierarchical Attention
FasterViT: Fast Vision Transformers with Hierarchical Attention
Ali Hatamizadeh
Greg Heinrich
Hongxu Yin
Andrew Tao
J. Álvarez
Jan Kautz
Pavlo Molchanov
ViT
102
71
0
09 Jun 2023
Structured Pruning for Deep Convolutional Neural Networks: A survey
Structured Pruning for Deep Convolutional Neural Networks: A survey
Yang He
Lingao Xiao
3DPC
82
137
0
01 Mar 2023
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of
  Specific Rigid Objects
BOP Challenge 2022 on Detection, Segmentation and Pose Estimation of Specific Rigid Objects
M. Sundermeyer
Tomás Hodan
Yann Labbé
Gu Wang
Eric Brachmann
Bertram Drost
Carsten Rother
Juan E. Sala Matas
3DPC
62
79
0
25 Feb 2023
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
ConvNeXt V2: Co-designing and Scaling ConvNets with Masked Autoencoders
Sanghyun Woo
Shoubhik Debnath
Ronghang Hu
Xinlei Chen
Zhuang Liu
In So Kweon
Saining Xie
SyDa
145
795
0
02 Jan 2023
A ConvNet for the 2020s
A ConvNet for the 2020s
Zhuang Liu
Hanzi Mao
Chaozheng Wu
Christoph Feichtenhofer
Trevor Darrell
Saining Xie
ViT
168
5,171
0
10 Jan 2022
YOLOX: Exceeding YOLO Series in 2021
YOLOX: Exceeding YOLO Series in 2021
Zheng Ge
Songtao Liu
Feng Wang
Zeming Li
Jian Sun
ObjD
136
4,090
0
18 Jul 2021
Towards Understanding Knowledge Distillation
Towards Understanding Knowledge Distillation
Mary Phuong
Christoph H. Lampert
65
319
0
27 May 2021
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in
  Knowledge Distillation
Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation
Taehyeon Kim
Jaehoon Oh
Nakyil Kim
Sangwook Cho
Se-Young Yun
51
234
0
19 May 2021
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Pruning and Quantization for Deep Neural Network Acceleration: A Survey
Tailin Liang
C. Glossner
Lei Wang
Shaobo Shi
Xiaotong Zhang
MQ
208
697
0
24 Jan 2021
BOP Challenge 2020 on 6D Object Localization
BOP Challenge 2020 on 6D Object Localization
Tomás Hodan
M. Sundermeyer
Bertram Drost
Yann Labbé
Eric Brachmann
Frank Michel
Carsten Rother
Jirí Matas
3DPC
80
266
0
15 Sep 2020
What is the State of Neural Network Pruning?
What is the State of Neural Network Pruning?
Davis W. Blalock
Jose Javier Gonzalez Ortiz
Jonathan Frankle
John Guttag
267
1,052
0
06 Mar 2020
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects
T-LESS: An RGB-D Dataset for 6D Pose Estimation of Texture-less Objects
Tomás Hodan
Pavel Haluza
Stepán Obdrzálek
Jirí Matas
Manolis I. A. Lourakis
Xenophon Zabulis
69
501
0
19 Jan 2017
Pruning Filters for Efficient ConvNets
Pruning Filters for Efficient ConvNets
Hao Li
Asim Kadav
Igor Durdanovic
H. Samet
H. Graf
3DPC
193
3,697
0
31 Aug 2016
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