Fetching the paper…
Reading the bibliography…
In this work, we explore how a strategic selection of camera movements can facilitate the task of 6D multi-object pose estimation in cluttered scenarios while respecting real-world constraints important in robotics and augmented reality applications, such as time and distance traveled.
Increasing pose estimation performance using multi-cue integration
F. Viksten, R. Soderberg, K. Nordberg, and C. Perwass · 2006
Earlier work this paper cites.
Model globally, match locally: Efficient and robust 3D object recognition
B. Drost, M. Ulrich, N. Navab, and S. Ilic · 2010
Earlier work this paper cites.
Efficient multi-view object recognition and full pose estimation
A. Collet and S. S. Srinivasa · 2010
Earlier work this paper cites.
Kinectfusion: real-time 3d reconstruction and interaction using a moving depth camera
S. Izadi, , et al · 2011
Earlier work this paper cites.
Multimodal templates for real-time detection of texture-less objects in heavily cluttered scenes
S. Hinterstoisser, S. Holzer, C. Cagniart, S. Ilic, K. Konolige, N. Navab, and V. Lepetit · 2011
Earlier work this paper cites.
A global hypotheses verification method for 3d object recognition
A. Aldoma, F. Tombari, L. Di Stefano, and M. Vincze · 2012
Earlier work this paper cites.
Model based training, detection and pose estimation of texture-less 3D objects in heavily cluttered scenes
S. Hinterstoisser, V. Lepetit, S. Ilic, S. Holzer, G. Bradski, K. Konolige, and N. Navab · 2012
Earlier work this paper cites.
Learning 6d object pose estimation using 3D object coordinates
E. Brachmann, A. Krull, F. Michel, S. Gumhold, J. Shotton, and C. Rother · 2014
Earlier work this paper cites.
Latent-class hough forests for 3D object detection and pose estimation
A. Tejani, D. Tang, R. Kouskouridas, and T.-K. Kim · 2014
Earlier work this paper cites.
An active search strategy for efficient object class detection
A. Gonzalez-Garcia, A. Vezhnevets, and V. Ferrari · 2015
Earlier work this paper cites.
Active object localization with deep reinforcement learning
J. C. Caicedo and S. Lazebnik · 2015
Earlier work this paper cites.
End-to-end training of deep visuomotor policies
S. Levine, C. Finn, T. Darrell, and P. Abbeel · 2016
Earlier work this paper cites.
Lessons from the amazon picking challenge: Four aspects of building robotic systems
C. Eppner, S. Höfer, R. Jonschkowski, R. Martin, A. Sieverling, V. Wall, and O. Brock · 2016
Earlier work this paper cites.
Recovering 6D object pose and predicting next-best-view in the crowd
A. Doumanoglou, R. Kouskouridas, S. Malassiotis, and T.-K. Kim · 2016
Earlier work this paper cites.
Integration of probabilistic pose estimates from multiple views
Ö. Erkent, D. Shukla, and J. Piater · 2016
Earlier work this paper cites.
Reinforcement learning for visual object detection
S. Mathe, A. Pirinen, and C. Sminchisescu · 2016
Cited alongside, same era.
Learning to navigate in complex environments
P. Mirowski et al · 2016
Cited alongside, same era.
3d attention-driven depth acquisition for object identification
K. Xu, Y. Shi, L. Zheng, J. Zhang, M. Liu, H. Huang, H. Su, D. Cohen-Or, and B. Chen · 2016
Cited alongside, same era.
Multi-view self-supervised deep learning for 6D pose estimation in the amazon picking challenge
A. Zeng, K.-T. Yu, S. Song, D. Suo, E. Walker, A. Rodriguez, and J. Xiao · 2017
Cited alongside, same era.
Multi-view 6d object pose estimation and camera motion planning using rgbd images
J. Sock, S. Hamidreza Kasaei, L. Seabra Lopes, and T.-K. Kim · 2017
Cited alongside, same era.
BB8: A scalable, accurate, robust to partial occlusion method for predicting the 3D poses of challenging objects without using depth
Symmetry aware evaluation of 3D object detection and pose estimation in scenes of many parts in bulk
R. Brégier, F. Devernay, L. Leyrit, and J. Crowley · 2017
Later among the works it cites.
Bop: benchmark for 6d object pose estimation
T. Hodan, F. Michel, E. Brachmann, W. Kehl, A. GlentBuch, D. Kraft, B. Drost, J. Vidal, S. Ihrke, X. Zabulis, et al · 2018
Later among the works it cites.
Multi-task deep networks for depth-based 6d object pose and joint registration in crowd scenarios
J. Sock, K. I. Kim, C. Sahin, and T.-K. Kim · 2018
Later among the works it cites.
Implicit 3d orientation learning for 6d object detection from rgb images
M. Sundermeyer, Z.-C. Marton, M. Durner, M. Brucker, and R. Triebel · 2018
Later among the works it cites.
Rotationnet: Joint object categorization and pose estimation using multiviews from unsupervised viewpoints
A. Kanezaki, Y. Matsushita, and Y. Nishida · 2018
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
M. Rad and V. Lepetit · 2017
Cited alongside, same era.
Real-time seamless single shot 6D object pose prediction
B. Tekin, S. Sinha, and P. Fua · 2017
Cited alongside, same era.
Pose guided rgbd feature learning for 3D object pose estimation
V. Balntas, A. Doumanoglou, C. Sahin, J. Sock, R. Kouskouridas, and T.-K. Kim · 2017
Cited alongside, same era.
SSD-6D: Making rgb-based 3D detection and 6D pose estimation great again
W. Kehl, F. Manhardt, F. Tombari, S. Ilic, and N. Navab · 2017
Cited alongside, same era.
Posecnn: A convolutional neural network for 6D object pose estimation in cluttered scenes
Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox · 2017
Cited alongside, same era.
Target-driven visual navigation in indoor scenes using deep reinforcement learning
Y. Zhu, R. Mottaghi, E. Kolve, J. J. Lim, A. Gupta, L. Fei-Fei, and A. Farhadi · 2017
Cited alongside, same era.
Cognitive mapping and planning for visual navigation
S. Gupta, J. Davidson, S. Levine, R. Sukthankar, and J. Malik · 2017
Cited alongside, same era.
A unified framework for multi-view multi-class object pose estimation
C. Li, J. Bai, and G. D. Hager · 2018
Later among the works it cites.
Active vision via extremum seeking for robots in unstructured environments: Applications in object recognition and manipulation
B. Calli, W. Caarls, M. Wisse, and P. P. Jonker · 2018
Later among the works it cites.
Active object reconstruction using a guided view planner
X. Yang, Y. Wang, Y. Wang, B. Yin, Q. Zhang, X. Wei, and H. Fu · 2018
Later among the works it cites.
Deep object-centric representations for generalizable robot learning
C. Devin, P. Abbeel, T. Darrell, and S. Levine · 2018
Later among the works it cites.
Deep object centric policies for autonomous driving
D. Wang, C. Devin, Q.-Z. Cai, F. Yu, and T. Darrell · 2018
Later among the works it cites.
First-person hand action benchmark with rgb-d videos and 3d hand pose annotations
G. Garcia-Hernando, S. Yuan, S. Baek, and T.-K. Kim · 2018
Later among the works it cites.
Task-oriented hand motion retargeting for dexterous manipulation imitation
D. Antotsiou, G. Garcia-Hernando, and T.-K. Kim · 2018
Later among the works it cites.
Instance-and category-level 6d object pose estimation
C. Sahin, G. Garcia-Hernando, J. Sock, and T.-K. Kim · 2019
Closest in time.
Pvnet: Pixel-wise voting network for 6dof pose estimation
S. Peng, Y. Liu, Q. Huang, H. Bao, and X. Zhou · 2019
Closest in time.
Normalized object coordinate space for category-level 6d object pose and size estimation
H. Wang, S. Sridhar, J. Huang, J. Valentin, S. Song, and L. J. Guibas · 2019
Closest in time.