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Computer vision (CV) is the process of using machines to understand and analyze imagery, which is an integral branch of artificial intelligence.
Finding frequent items in data streams
M. Charikar, K. Chen, and M. Farach-Colton · 2002
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Automated flower classification over a large number of classes
M.-E. Nilsback and A. Zisserman · 2008
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Novel dataset for fine-grained image categorization
A. Khosla, N. Jayadevaprakash, B. Yao, and L. Fei-Fei · 2011
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The Caltech-UCSD birds-200-2011 dataset
C. Wah, S. Branson, P. Welinder, P. Perona, and S. Belongie · 2011
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3D object representations for fine-grained categorization
J. Krause, M. Stark, J. Deng, and L. Fei-Fei · 2013
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Fine-grained visual classification of aircraft
S. Maji, J. Kannala, E. Rahtu, M. Blaschko, and A. Vedaldi · 2013
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Fast and scalable polynomial kernels via explicit feature maps
N. Pham and R. Pagh · 2013
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Birdsnap: Large-scale fine-grained visual categorization of birds
T. Berg, J. Liu, S. W. Lee, M. L. Alexander, D. W. Jacobs, and P. N. Belhumeur · 2014
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Generative adversarial nets
I. Goodfellow, J. Pouget-Abadie, M. Mirza, B. Xu, D. Warde-Farley, S. Ozair, A. Courville, and Y. Bengio · 2014
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Part-based R-CNNs for fine-grained category detection
N. Zhang, J. Donahue, R. Girshick, and T. Darrell · 2014
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Efficient and robust automated machine learning
M. Feurer, A. Klein, K. Eggensperger, J. Springenberg, M. Blum, and F. Hutter · 2015
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Spatial transformer networks
M. Jaderberg, K. Simonyan, A. Zisserman, and K. Kavukcuoglu · 2015
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Deep learning
Y. LeCun, Y. Bengion, and G. Hinton · 2015
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DBpedia - A large-scale, multilingual knowledge base extracted from Wikipedia
J. Lehmann, R. Isele, M. Jakob, A. Jentzsch, D. Kontokostas, P. N. Mendes, S. Hellmann, M. Morsey, P. van Kleef, S. Auer, and C. Bizer · 2015
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Deep LAC: Deep localization, alignment and classification for fine-grained recognition
D. Lin, X. Shen, C. Lu, and J. Jia · 2015
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Bilinear CNN models for fine-grained visual recognition
T.-Y. Lin, A. RoyChowdhury, and S. Maji · 2015
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Fine-grained categorization and dataset bootstrapping using deep metric learning with humans in the loop
Y. Cui, F. Zhou, Y. Lin, and S. Belongie · 2016
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Leveraging the wisdom of the crowd for fine-grained recognition
J. Deng, J. Krause, M. Stark, and L. Fei-Fei · 2016
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Compact bilinear pooling
Y. Gao, O. Beijbom, N. Zhang, and T. Darrell · 2016
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Feature learning based deep supervised hashing with pairwise labels
W.-J. Li, S. Wang, and W.-C. Kang · 2016
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DeepFashion: Powering robust clothes recognition and retrieval with rich annotations
Z. Liu, P. Luo, S. Qiu, X. Wang, and X. Tang · 2016
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Learning deep representations of fine-grained visual descriptions
S. Reed, Z. Akata, H. Lee, and B. Schiele · 2016
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CVAE-GAN: Fine-grained image generation through asymmetric training
J. Bao, D. Chen, F. Wen, H. Li, and G. Hua · 2017
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Kernel pooling for convolutional neural network
Y. Cui, F. Zhou, J. Wang, X. Liu, Y. Lin, and S. Belongie · 2017
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Maximum entropy fine-grained classification
A. Dubey, O. Gupta, R. Raskar, and N. Naik · 2018
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Neural architecture search: A survey
T. Elsken, J. H. Metzen, and F. Hutter · 2018
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Webly supervised learning meets zero-shot learning: A hybrid approach for fine-grained classification
L. Niu, A. Veeraraghavan, and A. Sabharwal · 2018
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Part-aligned bilinear representations for person re-identification
Y. Suh, J. Wang, S. Tang, T. Mei, and K. M. Lee · 2018
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Multi-attention multi-class constraint for fine-grained image recognition
M. Sun, Y. Yuan, F. Zhou, and E. Ding · 2018
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A survey on learning to hash
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Look closer to see better: Recurrent attention convolutional neural network for fine-grained image recognition
J. Fu, H. Zheng, and T. Mei · 2017
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Fine-grained image classification via combining vision and language
X. He and Y. Peng · 2017
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Weakly supervised learning of part selection model with spatial constraints for fine-grained image classification
X. He and Y. Peng · 2017
Cited alongside, same era.
The iNaturalist species classification and detection dataset
G. Van Horn, O. M. Aodha, Y. Song, Y. Cui, C. Sun, A. Shepard, H. Adam, P. Perona, and S. Belongie · 2017
Cited alongside, same era.
VegFru: A domain-specific dataset for fine-grained visual categorization
S. Hou, Y. Feng, and Z. Wang · 2017
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Low-rank bilinear pooling for fine-grained classification
S. Kong and C. Fowlkes · 2017
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J. Wang, T. Zhang, J. Song, N. Sebe, and H. T. Shen · 2018
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Mask-CNN: Localizing parts and selecting descriptors for fine-grained bird species categorization
X.-S. Wei, C.-W. Xie, J. Wu, and C. Shen · 2018
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Coarse-to-fine: A RNN-based hierarchical attention model for vehicle re-identification
X.-S. Wei, C.-L. Zhang, L. Liu, C. Shen, and J. Wu · 2018
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Fine-grained image classification by visual-semantic embedding
H. Xu, G. Qi, J. Li, M. Wang, K. Xu, and H. Gao · 2018
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AttnGAN: Fine-grained text to image generation with attentional generative adversarial networks
T. Xu, P. Zhang, Q. Huang, H. Zhang, Z. Gan, X. Huang, and X. He · 2018
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Learning to navigate for fine-grained classification
Z. Yang, T. Luo, D. Wang, Z. Hu, J. Gao, and L. Wang · 2018
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Fine-grained visual categorization using meta-learning optimization with sample selection of auxiliary data
Y. Zhang, H. Tang, and K. Jia · 2018
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Centralized ranking loss with weakly supervised localization for fine-grained object retrieval
X. Zheng, R. Ji, X. Sun, Y. Wu, F. Huang, and Y. Yang · 2018
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Learning from web data using adversarial discriminative neural networks for fine-grained classification
X. Sun, L. Chen, and J. Yang · 2019
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RPC: A large-scale retail product checkout dataset
X.-S. Wei, Q. Cui, L. Yang, P. Wang, and L. Liu · 2019
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Piecewise classifier mappings: Learning fine-grained learners for novel categories with few examples
X.-S. Wei, P. Wang, L. Liu, C. Shen, and J. Wu · 2019
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Towards optimal fine grained retrieval via decorrelated centralized loss with normalize-scale layer
X. Zheng, R. Ji, X. Sun, B. Zhang, Y. Wu, and F. Huang · 2019
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