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With the increasing performance of machine learning techniques in the last few years, the computer vision and robotics communities have created a large number of datasets for benchmarking object recognition tasks.
Labeled faces in the wild: A database for studying face recognition in unconstrained environments
G. B. Huang, M. Ramesh, T. Berg, and E. Learned-Miller · 2007
Earlier work this paper cites.
Recognizing groceries in situ using in vitro training data
M. Merler, C. Galleguillos, and S. Belongie · 2007
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
J. Deng, W. Dong, R. Socher, L.-J. Li, K. Li, and L. Fei-Fei · 2009
Earlier work this paper cites.
Learning multiple layers of features from tiny images
A. Krizhevsky and G. Hinton · 2009
Earlier work this paper cites.
The pascal visual object classes (voc) challenge
M. Everingham, L. Van Gool, C. K. Williams, J. Winn, and A. Zisserman · 2010
Earlier work this paper cites.
Making specific features less discriminative to improve point-based 3d object recognition
E. Hsiao, A. Collet, and M. Hebert · 2010
Earlier work this paper cites.
Herb: a home exploring robotic butler
S. S. Srinivasa, D. Ferguson, C. J. Helfrich, D. Berenson, A. Collet, R. Diankov, G. Gallagher, G. Hollinger, J. Kuffner, and M. V. Weghe · 2010
Earlier work this paper cites.
A large-scale hierarchical multi-view rgb-d object dataset
K. Lai, L. Bo, X. Ren, and D. Fox · 2011
Earlier work this paper cites.
Reading digits in natural images with unsupervised feature learning
Y. Netzer, T. Wang, A. Coates, A. Bissacco, B. Wu, and A. Y. Ng · 2011
Earlier work this paper cites.
Fast and robust object detection in household environments using vocabulary trees with sift descriptors
D. Pangercic, V. Haltakov, and M. Beetz · 2011
Earlier work this paper cites.
Indoor scene segmentation using a structured light sensor
N. Silberman and R. Fergus · 2011
Earlier work this paper cites.
3d descriptors for object and category recognition: a comparative evaluation
L. A. Alexandre · 2012
Earlier work this paper cites.
Unsupervised Feature Learning for RGB-D Based Object Recognition
L. Bo, X. Ren, and D. Fox · 2012
Cited alongside, same era.
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
Cited alongside, same era.
The kit object models database: An object model database for object recognition, localization and manipulation in service robotics
A. Kasper, Z. Xue, and R. Dillmann · 2012
Cited alongside, same era.
Imagenet classification with deep convolutional neural networks
A. Krizhevsky, I. Sutskever, and G. E. Hinton · 2012
Cited alongside, same era.
Cloud-based robot grasping with the google object recognition engine
B. Kehoe, A. Matsukawa, S. Candido, J. Kuffner, and K. Goldberg · 2013
Cited alongside, same era.
Robosherlock: unstructured information processing for robot perception
M. Beetz, F. Bálint-Benczédi, N. Blodow, D. Nyga, T. Wiedemeyer, and Z.-C. Márton · 2015
Later among the works it cites.
Benchmarking in manipulation research: The ycb object and model set and benchmarking protocols
B. Calli, A. Walsman, A. Singh, S. Srinivasa, P. Abbeel, and A. M. Dollar · 2015
Later among the works it cites.
Multimodal deep learning for robust rgb-d object recognition
A. Eitel, J. T. Springenberg, L. Spinello, M. Riedmiller, and W. Burgard · 2015
Later among the works it cites.
Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
K. He, X. Zhang, S. Ren, and J. Sun · 2015
Later among the works it cites.
Batch normalization: Accelerating deep network training by reducing internal covariate shift
S. Ioffe and C. Szegedy · 2015
Later among the works it cites.
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Y. Jia, E. Shelhamer, J. Donahue, S. Karayev, J. Long, R. Girshick, S. Guadarrama, and T. Darrell · 2014
Cited alongside, same era.
Extracting common sense knowledge from text for robot planning
P. Kaiser, M. Lewis, R. Petrick, T. Asfour, and M. Steedman · 2014
Cited alongside, same era.
Microsoft coco: Common objects in context
T.-Y. Lin, M. Maire, S. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick · 2014
Cited alongside, same era.
Bigbird: A large-scale 3d database of object instances
A. Singh, J. Sha, K. S. Narayan, T. Achim, and P. Abbeel · 2014
Cited alongside, same era.
Deepface: Closing the gap to human-level performance in face verification
Y. Taigman, M. Yang, M. Ranzato, and L. Wolf · 2014
Cited alongside, same era.
Learning deep features for scene recognition using places database
B. Zhou, A. Lapedriza, J. Xiao, A. Torralba, and A. Oliva · 2014
Cited alongside, same era.
Simtrack: A simulation-based framework for scalable real-time object pose detection and tracking
K. Pauwels and D. Kragic · 2015
Later among the works it cites.
IAI Kinect2, 2014 – 2015
T. Wiedemeyer · 2015
Later among the works it cites.
Organizing objects by predicting user preferences through collaborative filtering
N. Abdo, C. Stachniss, L. Spinello, and W. Burgard · 2016
Closest in time.
Open food facts
S. Gigandet · 2016
Closest in time.
A dataset for improved rgbd-based object detection and pose estimation for warehouse pick-and-place
C. Rennie, R. Shome, K. E. Bekris, and A. F. De Souza · 2016
Closest in time.
libfreenect2: Release 0.2, 2016
L. Xiang, F. Echtler, C. Kerl, T. Wiedemeyer, Lars, hanyazou, R. Gordon, F. Facioni, laborer2008, R. Wareham, M. Goldhoorn, alberth, gaborpapp, S. Fuchs, jmtatsch, J. Blake, Federico, H. Jungkurth, Y. Mingze, vinouz, D. Coleman, B. Burns, R. Rawat, S. Mokhov, P. Reynolds, P. Viau, M. Fraissinet-Tachet, Ludique, J. Billingham, and Alistair · 2016
Closest in time.