Fetching the paper…
Reading the bibliography…
We introduce MegaPose, a method to estimate the 6D pose of novel objects, that is, objects unseen during training.
Machine perception of three-dimensional solids
L. G. Roberts · 1963
Earlier work this paper cites.
Three-dimensional object recognition from single two-dimensional images
D. G. Lowe · 1987
Earlier work this paper cites.
Method for registration of 3-d shapes
P. J. Besl and N. D. McKay · 1992
Earlier work this paper cites.
Iterative point matching for registration of free-form curves and surfaces
Z. Zhang · 1994
Earlier work this paper cites.
Object recognition from local scale-invariant features
D. G. Lowe · 1999
Earlier work this paper cites.
A simple and efficient template matching algorithm
F. Jurie and M. Dhome · 2001
Earlier work this paper cites.
Multiple View Geometry in Computer Vision
R. I. Hartley and A. Zisserman · 2004
Earlier work this paper cites.
SURF: Speeded up robust features
H. Bay, T. Tuytelaars, and L. Van Gool · 2006
Earlier work this paper cites.
EPnP: An accurate O(n) solution to the PnP problem
V. Lepetit, F. Moreno-Noguer, and P. Fua · 2009
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.
The MOPED framework: Object recognition and pose estimation for manipulation
A. Collet, M. Martinez, and S. S. Srinivasa · 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.
AprilTag: A robust and flexible visual fiducial system
E. Olson · 2011
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.
Seeing 3D chairs: Exemplar part-based 2D-3D alignment using a large dataset of CAD models
M. Aubry, D. Maturana, A. A. Efros, B. Russell, and J. Sivic · 2014
Earlier work this paper cites.
3d shapenets: A deep representation for volumetric shapes
Z. Wu, S. Song, A. Khosla, F. Yu, L. Zhang, X. Tang, and J. Xiao · 2015
Earlier work this paper cites.
Simtrack: A simulation-based framework for scalable real-time object pose detection and tracking
K. Pauwels and D. Kragic · 2015
Earlier work this paper cites.
Training a feedback loop for hand pose estimation
M. Oberweger, P. Wohlhart, and V. Lepetit · 2015
Earlier work this paper cites.
ShapeNet: An Information-Rich 3D Model Repository
A. X. Chang, T. Funkhouser, L. Guibas, P. Hanrahan, Q. Huang, Z. Li, S. Savarese, M. Savva, S. Song, H. Su, J. Xiao, L. Yi, and F. Yu · 2015
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.
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
Earlier work this paper cites.
BB8: A scalable, accurate, robust to partial occlusion method for predicting the 3D poses of challenging objects without using depth
M. Rad and V. Lepetit · 2017
Earlier work this paper cites.
6-dof object pose from semantic keypoints
G. Pavlakos, X. Zhou, A. Chan, K. G. Derpanis, and K. Daniilidis · 2017
Earlier work this paper cites.
T-LESS: An RGB-D dataset for 6D pose estimation of Texture-Less objects
T. Hodan, P. Haluza, Š. Obdržálek, J. Matas, M. Lourakis, and X. Zabulis · 2017
Cited alongside, same era.
Introducing mvtec itodd-a dataset for 3d object recognition in industry
B. Drost, M. Ulrich, P. Bergmann, P. Hartinger, and C. Steger · 2017
Cited alongside, same era.
DeepIM: Deep iterative matching for 6D pose estimation
Y. Li, G. Wang, X. Ji, Y. Xiang, and D. Fox · 2018
Cited alongside, same era.
Deep object pose estimation for semantic robotic grasping of household objects
J. Tremblay, T. To, B. Sundaralingam, Y. Xiang, D. Fox, and S. Birchfield · 2018
Cited alongside, same era.
Real-time seamless single shot 6d object pose prediction
B. Tekin, S. N. Sinha, and P. Fua · 2018
Cited alongside, same era.
PoseCNN: A convolutional neural network for 6D object pose estimation in cluttered scenes
F. Manhardt, G. Wang, B. Busam, M. Nickel, S. Meier, L. Minciullo, X. Ji, and N. Navab · 2020
Later among the works it cites.
LatentFusion: End-to-end differentiable reconstruction and rendering for unseen object pose estimation
K. Park, A. Mousavian, Y. Xiang, and D. Fox · 2020
Later among the works it cites.
Multi-path learning for object pose estimation across domains
M. Sundermeyer, M. Durner, E. Y. Puang, Z.-C. Marton, N. Vaskevicius, K. O. Arras, and R. Triebel · 2020
Later among the works it cites.
Os2d: One-stage one-shot object detection by matching anchor features
A. Osokin, D. Sumin, and V. Lomakin · 2020
Later among the works it cites.
Few-shot object detection and viewpoint estimation for objects in the wild
Y. Xiao and R. Marlet · 2020
Later among the works it cites.
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Y. Xiang, T. Schmidt, V. Narayanan, and D. Fox · 2018
Cited alongside, same era.
Deep model-based 6d pose refinement in rgb
F. Manhardt, W. Kehl, N. Navab, and F. Tombari · 2018
Cited alongside, same era.
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
Cited alongside, same era.
Dex-net 3.0: Computing robust vacuum suction grasp targets in point clouds using a new analytic model and deep learning
J. Mahler, M. Matl, X. Liu, A. Li, D. Gealy, and K. Goldberg · 2018
Cited alongside, same era.
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
Cited alongside, same era.
KPAM: Keypoint affordances for category-level robotic manipulation
L. Manuelli, W. Gao, P. Florence, and R. Tedrake · 2019
Cited alongside, same era.
Pose from shape: Deep pose estimation for arbitrary 3D objects
Y. Xiao, X. Qiu, P.-A. Langlois, M. Aubry, and R. Marlet · 2019
Cited alongside, same era.
Hybridpose: 6D object pose estimation under hybrid representations
C. Song, J. Song, and Q. Huang · 2020
Later among the works it cites.
se (3)-tracknet: Data-driven 6d pose tracking by calibrating image residuals in synthetic domains
B. Wen, C. Mitash, B. Ren, and K. E. Bekris · 2020
Later among the works it cites.
GDR-Net: Geometry-guided direct regression network for monocular 6D object pose estimation
G. Wang, F. Manhardt, F. Tombari, and X. Ji · 2021
Later among the works it cites.
Catgrasp: Learning category-level task-relevant grasping in clutter from simulation
B. Wen, W. Lian, K. Bekris, and S. Schaal · 2021
Later among the works it cites.
ZePHyR: Zero-shot pose hypothesis rating
B. Okorn, Q. Gu, M. Hebert, and D. Held · 2021
Later among the works it cites.
Deep template-based object instance detection
J.-P. Mercier, M. Garon, P. Giguere, and J.-F. Lalonde · 2021
Later among the works it cites.
PoseContrast: Class-agnostic object viewpoint estimation in the wild with pose-aware contrastive learning
Y. Xiao, Y. Du, and R. Marlet · 2021
Later among the works it cites.
Unseen object instance segmentation for robotic environments
C. Xie, Y. Xiang, A. Mousavian, and D. Fox · 2021
Later among the works it cites.
Surfemb: Dense and continuous correspondence distributions for object pose estimation with learnt surface embeddings
R. L. Haugaard and A. G. Buch · 2022
Closest in time.
Coupled iterative refinement for 6D multi-object pose estimation
L. Lipson, Z. Teed, A. Goyal, and J. Deng · 2022
Closest in time.
Google scanned objects: A high-quality dataset of 3D scanned household items
L. Downs, A. Francis, N. Koenig, B. Kinman, R. Hickman, K. Reymann, T. B. McHugh, and V. Vanhoucke · 2022
Closest in time.
Single-stage keypoint-based category-level object pose estimation from an RGB image
Y. Lin, J. Tremblay, S. Tyree, P. A. Vela, and S. Birchfield · 2022
Closest in time.
Polarmesh: A star-convex 3d shape approximation for object pose estimation
F. Li, I. Shugurov, B. Busam, M. Li, S. Yang, and S. Ilic · 2022
Closest in time.
OSOP: A multi-stage one shot object pose estimation framework
I. Shugurov, F. Li, B. Busam, and S. Ilic · 2022
Closest in time.
Templates for 3D object pose estimation revisited: Generalization to new objects and robustness to occlusions
V. N. Nguyen, Y. Hu, Y. Xiao, M. Salzmann, and V. Lepetit · 2022
Closest in time.
Gen6D: Generalizable model-free 6-DoF object pose estimation from RGB images
Y. Liu, Y. Wen, S. Peng, C. Lin, X. Long, T. Komura, and W. Wang · 2022
Closest in time.
FS6D: Few-shot 6D pose estimation of novel objects
Y. He, Y. Wang, H. Fan, J. Sun, and Q. Chen · 2022
Closest in time.
OnePose: One-shot object pose estimation without CAD models
J. Sun, Z. Wang, S. Zhang, X. He, H. Zhao, G. Zhang, and X. Zhou · 2022
Closest in time.