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This paper introduces Amazon Robotic Manipulation Benchmark (ARMBench), a large-scale, object-centric benchmark dataset for robotic manipulation in the context of a warehouse.
1906
Earlier work this paper cites.
C. Fellbaum, Ed., WordNet: An Electronic Lexical Database , ser. Language, Speech, and Communication. Cambridge, MA: MIT Press, 1998
1998
Earlier work this paper cites.
J. Sivic and A. Zisserman, “Video google: A text retrieval approach to object matching in videos,” in null . IEEE, 2003, p. 1470
2003
Earlier work this paper cites.
“DAGM 2007,” July 2022, [Online; accessed 12. Jul. 2022]. [Online]. Available: https://conferences.mpi-inf.mpg.de/dagm/2007/prizes.html
2007
Earlier work this paper cites.
J. Philbin, O. Chum, M. Isard, J. Sivic, and A. Zisserman, “Object retrieval with large vocabularies and fast spatial matching,” in 2007 IEEE conference on computer vision and pattern recognition . IEEE, 2007, pp. 1–8
2007
Earlier work this paper cites.
——, “Lost in quantization: Improving particular object retrieval in large scale image databases,” in 2008 IEEE conference on computer vision and pattern recognition . IEEE, 2008, pp. 1–8
2008
Earlier work this paper cites.
M. Everingham, L. V. Gool, C. K. I. Williams, J. Winn, and A. Zisserman, “The pascal visual object classes (voc) challenge,” International Journal of Computer Vision , vol. 88, pp. 303–308, September 2009, printed version publication date: June 2010
2010
Earlier work this paper cites.
H. Jégou, M. Douze, C. Schmid, and P. Pérez, “Aggregating local descriptors into a compact image representation,” in 2010 IEEE computer society conference on computer vision and pattern recognition . IEEE, 2010, pp. 3304–3311
2010
Earlier work this paper cites.
H. Liao, T. Inomata, I. Sakuma, and T. Dohi, “3-d augmented reality for mri-guided surgery using integral videography autostereoscopic image overlay,” IEEE Transactions on Biomedical Engineering , vol. 57, no. 6, pp. 1476–1486, 2010
2010
Earlier work this paper cites.
W. Li, V. Mahadevan, and N. Vasconcelos, “Anomaly detection and localization in crowded scenes,” IEEE transactions on pattern analysis and machine intelligence , vol. 36, no. 1, pp. 18–32, 2013
2013
Earlier work this paper cites.
A. Babenko, A. Slesarev, A. Chigorin, and V. Lempitsky, “Neural codes for image retrieval,” in European conference on computer vision . Springer, 2014, pp. 584–599
2014
Earlier work this paper cites.
E. Brachmann, A. Krull, F. Michel, S. Gumhold, J. Shotton, and C. Rother, “Learning 6d object pose estimation using 3d object coordinates,” in ECCV , 2014
2014
Earlier work this paper cites.
A. Karpathy, G. Toderici, S. Shetty, T. Leung, R. Sukthankar, and L. Fei-Fei, “Large-scale video classification with convolutional neural networks,” in Proceedings of the IEEE conference on Computer Vision and Pattern Recognition , 2014, pp. 1725–1732
2014
Earlier work this paper cites.
T.-Y. Lin, M. Maire, S. J. Belongie, J. Hays, P. Perona, D. Ramanan, P. Dollár, and C. L. Zitnick, “Microsoft coco: Common objects in context,” in ECCV , 2014
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
O. Russakovsky, J. Deng, H. Su, J. Krause, S. Satheesh, S. Ma, Z. Huang, A. Karpathy, A. Khosla, M. Bernstein, et al. , “Imagenet large scale visual recognition challenge,” International journal of computer vision , vol. 115, no. 3, pp. 211–252, 2015
2015
Earlier work this paper cites.
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
N. Correll, K. E. Bekris, D. Berenson, O. Brock, A. Causo, K. Hauser, K. Okada, A. Rodriguez, J. M. Romano, and P. R. Wurman, “Analysis and observations from the first amazon picking challenge,” IEEE Transactions on Automation Science and Engineering , vol. 15, no. 1, pp. 172–188, 2016
2016
Earlier work this paper cites.
Z. Liu, P. Luo, S. Qiu, X. Wang, and X. Tang, “Deepfashion: Powering robust clothes recognition and retrieval with rich annotations,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 1096–1104
2016
Earlier work this paper cites.
H. Oh Song, Y. Xiang, S. Jegelka, and S. Savarese, “Deep metric learning via lifted structured feature embedding,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2016, pp. 4004–4012
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
C. Rennie, R. Shome, K. E. Bekris, and A. F. de Souza, “A dataset for improved rgbd-based object detection and pose estimation for warehouse pick-and-place,” IEEE Robotics and Automation Letters , vol. 1, pp. 1179–1185, 2016
2016
Cited alongside, same era.
G. Tolias, Y. Avrithis, and H. Jégou, “Image search with selective match kernels: aggregation across single and multiple images,” International Journal of Computer Vision , vol. 116, no. 3, pp. 247–261, 2016
2016
Cited alongside, same era.
2016
Cited alongside, same era.
W. Abdulla, “Mask R-CNN for object detection and instance segmentation on keras and tensorflow,” https://github.com/matterport/Mask˙RCNN , 2017
2017
Cited alongside, same era.
P. Bergmann, M. Fauser, D. Sattlegger, and C. Steger, “MVTec AD–A comprehensive real-world dataset for unsupervised anomaly detection,” in 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) , 2019, pp. 9584–9592
2019
Later among the works it cites.
——, “Segmenting unknown 3d objects from real depth images using mask r-cnn trained on synthetic data,” in Proc. IEEE Int. Conf. Robotics and Automation (ICRA) , 2019
2019
Later among the works it cites.
N. Garcia and G. Vogiatzis, “Learning non-metric visual similarity for image retrieval,” Image and Vision Computing , vol. 82, pp. 18–25, 2019
2019
Later among the works it cites.
Y. Ge, R. Zhang, X. Wang, X. Tang, and P. Luo, “Deepfashion2: A versatile benchmark for detection, pose estimation, segmentation and re-identification of clothing images,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2019, pp. 5337–5345
2019
Later among the works it cites.
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B. Calli, A. Singh, J. Bruce, A. Walsman, K. Konolige, S. Srinivasa, P. Abbeel, and A. M. Dollar, “Yale-cmu-berkeley dataset for robotic manipulation research,” The International Journal of Robotics Research , vol. 36, no. 3, pp. 261–268, 2017
2017
Cited alongside, same era.
B. De Brabandere, D. Neven, and L. Van Gool, “Semantic instance segmentation for autonomous driving,” in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) , 2017, pp. 478–480
2017
Cited alongside, same era.
C. Eppner, S. Höfer, R. Jonschkowski, R. Martín-Martín, A. Sieverling, V. Wall, and O. Brock, “Lessons from the amazon picking challenge: Four aspects of building robotic systems,” in IJCAI , 2017
2017
Cited alongside, same era.
V. Gajjar, A. Gurnani, and Y. Khandhediya, “Human detection and tracking for video surveillance a cognitive science approach,” 2017
2017
Cited alongside, same era.
2017
Cited alongside, same era.
T. Hodan, P. Haluza, S. Obdrzálek, J. Matas, M. I. A. Lourakis, and X. Zabulis, “T-less: An rgb-d dataset for 6d pose estimation of texture-less objects,” 2017 IEEE Winter Conference on Applications of Computer Vision (WACV) , pp. 880–888, 2017
2017
Cited alongside, same era.
2017
Cited alongside, same era.
J. Leitner, A. W. Tow, N. Sünderhauf, J. E. Dean, J. W. Durham, M. Cooper, M. Eich, C. F. Lehnert, R. Mangels, C. McCool, P. T. Kujala, L. Nicholson, T. T. Pham, J. Sergeant, L. Wu, F. Zhang, B. Upcroft, and P. Corke, “The acrv picking benchmark: A robotic shelf picking benchmark to foster reproducible research,” 2017 IEEE International Conference on Robotics and Automation (ICRA) , pp. 4705–4712, 2017
2017
Cited alongside, same era.
2019
Later among the works it cites.
H. Lin, B. Li, X. Wang, Y. Shu, and S. Niu, “Automated defect inspection of LED chip using deep convolutional neural network,” Journal of Intelligent Manufacturing , vol. 30, no. 6, pp. 2525–2534, 2019
2019
Later among the works it cites.
J. Silvestre-Blanes, T. Albero-Albero, I. Miralles, R. Pérez-Llorens, and J. Moreno, “A public fabric database for defect detection methods and results,” Autex Research Journal , vol. 19, no. 4, pp. 363–374, 2019. [Online]. Available: https://doi.org/10.2478/aut-2019-0035
2019
Later among the works it cites.
2019
Later among the works it cites.
2020
Later among the works it cites.
L. Cheng, X. Zhou, L. Zhao, D. Li, H. Shang, Y. Zheng, P. Pan, and Y. Xu, “Weakly supervised learning with side information for noisy labeled images,” in European Conference on Computer Vision . Springer, 2020, pp. 306–321
2020
Later among the works it cites.
A. Diba, M. Fayyaz, V. Sharma, M. Paluri, J. Gall, R. Stiefelhagen, and L. V. Gool, “Large scale holistic video understanding,” in European Conference on Computer Vision . Springer, 2020, pp. 593–610
2020
Later among the works it cites.
2020
Later among the works it cites.
2020
Later among the works it cites.
T. Weyand, A. Araujo, B. Cao, and J. Sim, “Google landmarks dataset v2-a large-scale benchmark for instance-level recognition and retrieval,” in Proceedings of the IEEE/CVF conference on computer vision and pattern recognition , 2020, pp. 2575–2584
2020
Later among the works it cites.
Y. Bao, K. Song, J. Liu, Y. Wang, Y. Yan, H. Yu, and X. Li, “Triplet-graph reasoning network for few-shot metal generic surface defect segmentation,” IEEE Transactions on Instrumentation and Measurement , vol. 70, pp. 1–11, 2021
2021
Later among the works it cites.
B. Calli, A. Dollar, M. A. Roa, S. Srinivasa, and Y. Sun, “Guest editorial: Introduction to the special issue on benchmarking protocols for robotic manipulation,” IEEE Robotics and Automation Letters , vol. 6, no. 4, pp. 8678–8680, 2021
2021
Later among the works it cites.
M. Caron, H. Touvron, I. Misra, H. Jégou, J. Mairal, P. Bojanowski, and A. Joulin, “Emerging properties in self-supervised vision transformers,” in Proceedings of the International Conference on Computer Vision (ICCV) , 2021
2021
Later among the works it cites.
H. Fan, B. Xiong, K. Mangalam, Y. Li, Z. Yan, J. Malik, and C. Feichtenhofer, “Multiscale vision transformers,” 2021 IEEE/CVF International Conference on Computer Vision (ICCV) , pp. 6804–6815, 2021
2021
Later among the works it cites.
2021
Later among the works it cites.
C. Xie, Y. Xiang, A. Mousavian, and D. Fox, “Unseen object instance segmentation for robotic environments,” IEEE Transactions on Robotics , vol. 37, no. 5, pp. 1343–1359, 2021
2021
Later among the works it cites.
J. Collins, S. Goel, K. Deng, A. Luthra, L. Xu, E. Gundogdu, X. Zhang, T. F. Y. Vicente, T. Dideriksen, H. Arora, et al. , “Abo: Dataset and benchmarks for real-world 3d object understanding,” in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2022, pp. 21 126–21 136
2022
Later among the works it cites.