Fetching the paper…
Reading the bibliography…
Key information extraction from document images is of paramount importance in office automation.
F. Cesarini, E. Francesconi, M. Gori, and G. Soda, “Analysis and understanding of multi-class invoices,” Document Analysis and Recognition , vol. 6, no. 2, pp. 102–114, 2003
2003
Earlier work this paper cites.
J. Sivic and A. Zisserman, “Video google: A text retrieval approach to object matching in videos.” in ICCV , 2003, pp. 1470–1477
2003
Earlier work this paper cites.
E. Medvet, A. Bartoli, and G. Davanzo, “A probabilistic approach to printed document understanding,” International Journal on Document Analysis and Recognition (IJDAR) , vol. 14, no. 4, pp. 335–347, 2011
2011
Earlier work this paper cites.
D. Schuster, K. Muthmann, D. Esser, A. Schill, M. Berger, C. Weidling, K. Aliyev, and A. Hofmeier, “Intellix - End-User Trained Information Extraction for Document Archiving,” in ICDAR , 2013
2013
Earlier work this paper cites.
M. Rusiñol, T. Benkhelfallah, and V. P. dAndecy, “Field extraction from administrative documents by incremental structural templates,” in 2013 12th International Conference on Document Analysis and Recognition , 2013, pp. 1100–1104
2013
Earlier work this paper cites.
2014
Earlier work this paper cites.
D. K. Duvenaud, D. Maclaurin, J. Iparraguirre, R. Bombarell, T. Hirzel, A. Aspuru-Guzik, and R. P. Adams, “Convolutional networks on graphs for learning molecular fingerprints,” in NeurIPS , 2015, pp. 2224–2232
2015
Earlier work this paper cites.
R. Girshick, “Fast r-cnn,” in ICCV , 2015
2015
Earlier work this paper cites.
O. Ronneberger, P.Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in Medical Image Computing and Computer-Assisted Intervention (MICCAI) , vol. 9351, 2015, pp. 234–241
2015
Earlier work this paper cites.
2016
Earlier work this paper cites.
J. P. Chiu and E. Nichols, “Named entity recognition with bidirectional lstm-cnns,” Transactions of the Association for Computational Linguistics , vol. 4, pp. 357–370, 2016
2016
Earlier work this paper cites.
2016
Earlier work this paper cites.
W. Luo, Y. Li, R. Urtasun, and R. Zemel, “Understanding the effective receptive field in deep convolutional neural networks,” in Advances in Neural Information Processing Systems 29 , D. D. Lee, M. Sugiyama, U. V. Luxburg, I. Guyon, and R. Garnett, Eds., 2016, pp. 4898–4906
2016
Earlier work this paper cites.
H. Dai, B. Dai, and L. Song, “Discriminative embeddings of latent variable models for structured data,” in ICML , 2016, pp. 2702–2711
2016
Cited alongside, same era.
B. Ni, X. Yang, and S. Gao, “Progressively parsing interactional objects for fine grained action detection,” in CVPR , 2016, pp. 1020–1028
2016
Cited alongside, same era.
2016
Cited alongside, same era.
S. Sukhbaatar, A. Szlam, and R. Fergus, “Learning multiagent communication with backpropagation,” in NeurIPS , 2016, pp. 2244–2252
2016
Cited alongside, same era.
X. Liang, X. Shen, J. Feng, L. Lin, and S. Yan, “Semantic Object Parsing with Graph LSTM,” in ECCV , 2016
2016
Cited alongside, same era.
V. P. D’Andecy, E. Hartmann, and M. Rusinol, “Field extraction by hybrid incremental and a-priori structural templates,” in 2018 13th IAPR International Workshop on Document Analysis Systems (DAS) , 2018, pp. 251–256
2018
Later among the works it cites.
A. R. K. Faddoul, C. R. C. Guder, S. Brarda, S. Bickel, J. Höhne, and J. Baptiste, “Chargrid: Towards Understanding 2D Documents,” in EMNLP , 2018
2018
Later among the works it cites.
2018
Later among the works it cites.
S. Yan, Y. Xiong, and D. Lin, “Spatial temporal graph convolutional networks for skeleton-based action recognition,” in AAAI , 2018
2018
Later among the works it cites.
X. Wang and A. Gupta, “Videos as space-time region graphs,” in ECCV , 2018, pp. 399–417
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. Fukui, D. H. Park, D. Yang, A. Rohrbach, T. Darrell, and M. Rohrbach, “Multimodal Compact Bilinear Pooling for Visual Question Answering and Visual Grounding,” in EMNLP , 2016, pp. 457–468
2016
Cited alongside, same era.
R. B. Palm, O. Winther, and F. Laws, “Cloudscan-a configuration-free invoice analysis system using recurrent neural networks,” in ICDAR , vol. 1, 2017, pp. 406–413
2017
Cited alongside, same era.
A. Fornés, V. Romero, A. Baró, J. I. Toledo, J. A. Sánchez, E. Vidal, and J. Lladós, “Icdar2017 competition on information extraction in historical handwritten records,” in ICDAR , vol. 1, 2017, pp. 1389–1394
2017
Cited alongside, same era.
N. Peng, H. Poon, C. Quirk, K. Toutanova, and W.-t. Yih, “Cross-sentence n-ary relation extraction with graph lstms,” Transactions of the Association for Computational Linguistics , vol. 5, pp. 101–115, 2017
2017
Cited alongside, same era.
Y. Hoshen, “Vain: Attentional multi-agent predictive modeling,” in NeurIPS , 2017, pp. 2701–2711
2017
Cited alongside, same era.
D. Teney, L. Liu, and A. v. D. Hengel, “Graph-Structured Representations for Visual Question Answering,” in CVPR , 2017, pp. 1–9
2017
Cited alongside, same era.
J. H. Kim, K. W. On, W. Lim, J. Kim, J. W. Ha, and B. T. Zhang, “Hadamard Product for Low-rank Bilinear Pooling,” in ICLR , 2017, pp. 1–14
2017
Cited alongside, same era.
2018
Later among the works it cites.
2018
Later among the works it cites.
T. Chen, Z. Wang, G. Li, and L. Lin, “Recurrent Attentional Reinforcement Learning for Multi-label Image Recognition,” in AAAI , 2018
2018
Later among the works it cites.
J. Ye, L. Wang, G. Li, D. Chen, S. Zhe, X. Chu, and Z. Xu, “Learning compact recurrent neural networks with block-term tensor decomposition,” in CVPR , 2018, pp. 9378–9387
2018
Later among the works it cites.
P. VeliAkoviA, G. Cucurull, A. Casanova, A. Romero, P. LiA, and Y. Bengio, “Graph attention networks,” in International Conference on Learning Representations , 2018
2018
Later among the works it cites.
Z. Huang, K. Chen, J. He, X. Bai, D. Karatzas, S. Lu, and C. V. Jawahar, “ICDAR 2019 Robust Reading Challenge on Scanned Receipts OCR and Information Extraction,” 2019
2019
Later among the works it cites.
X. Liu, F. Gao, Q. Zhang, and H. Zhao, “Graph Convolution for Multimodal Information Extraction from Visually Rich Documents,” in NAACL , 2019, pp. 32–39
2019
Later among the works it cites.
Z. Kuang, Y. Gao, G. Li, P. Luo, Y. Chen, L. Lin, and W. Zhang, “Fashion Retrieval via Graph Reasoning Networks on a Similarity Pyramid,” in ICCV , 2019
2019
Later among the works it cites.
H. Ben-younes, R. Cadene, N. Thome, and M. Cord, “BLOCK: Bilinear Superdiagonal Fusion for Visual Question Answering and Visual Relationship Detection,” in AAAI , vol. 33, 2019, pp. 8102–8109
2019
Later among the works it cites.