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State-of-the-art visual perception models for a wide range of tasks rely on supervised pretraining.
Introductory lectures on convex optimization: A basic course
Nesterov, Y.: · 2004
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Hamming embedding and weak geometry consistency for large scale image search
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About WordNet
WordNet: · 2010
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Product quantization for nearest neighbor search
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Size matters: Exhaustive geometric verification for image retrieval
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Distributed representations of words and phrases and their compositionality
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Optimized product quantization
Ge, T., He, K., Ke, Q., Sun, J.: · 2013
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Rich feature hierarchies for accurate object detection and semantic segmentation
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Concreteness ratings for 40 thousand generally known english word lemmas
Brysbaert, M., Warriner, A.B., Kuperman, V.: · 2014
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Fully convolutional networks for semantic segmentation
Long, J., Shelhamer, E., Darrell, T.: · 2015
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Predicting depth, surface normals and semantic labels with a common multi-scale convolutional architecture
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ImageNet Large Scale Visual Recognition Challenge
Russakovsky, O., Deng, J., Su, H., Krause, J., Satheesh, S., Ma, S., Huang, Z., Karpathy, A., Khosla, A., Bernstein, M., Berg, A.C., Fei-Fei, L.: · 2015
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Ioffe, S., Szegedy, C.: · 2015
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Delving deep into rectifiers: Surpassing human-level performance on imagenet classification
He, K., Zhang, X., Ren, S., Sun, J.: · 2015
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User conditional hashtag prediction for images
Denton, E., Weston, J., Paluri, M., Bourdev, L., Fergus, R.: · 2015
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Facenet: A unified embedding for face recognition and clustering
Schroff, F., Kalenichenko, D., Philbin, J.: · 2015
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Web-scale training for face identification
Taigman, Y., Yang, M., Ranzato, M., Wolf, L.: · 2015
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What makes ImageNet good for transfer learning?
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Learning visual features from large weakly supervised data
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Towards accurate multi-person pose estimation in the wild
Papandreou, G., Zhu, T., Kanazawa, N., Toshev, A., Tompson, J., Bregler, C., Murphy, K.: · 2017
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Quo vadis, action recognition? a new model and the kinetics dataset
Carreira, J., Zisserman, A.: · 2017
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Places: A 10 million image database for scene recognition
Zhou, B., Lapedriza, A., Khosla, A., Oliva, A., Torralba, A.: · 2017
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Aggregated residual transformations for deep neural networks
Xie, S., Girshick, R., Dollar, P., Tu, Z., He, K.: · 2017
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Revisiting unreasonable effectiveness of data in deep learning era
Sun, C., Shrivastava, A., Singh, S., Gupta, A.: · 2017
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Deep image retrieval: Learning global representations for image search
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Particular object retrieval with integral max-pooling of cnn activations
Tolias, G., Sicre, R., , Jegou, H.: · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S., Sun, J.: · 2016
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Inception-v4, inception-resnet and the impact of residual connections on learning
Szegedy, C., Ioffe, S., Vanhoucke, V., Alemi, A.: · 2016
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Yfcc100m: The new data in multimedia research
Thomee, B., Shamma, D.A., Friedland, G., Elizalde, B., Ni, K., Poland, D., Borth, D., Li, L.J.: · 2016
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Goyal, P., Dollar, P., Girshick, R., Noordhuis, P., Wesolowski, L., Kyrola, A., Tulloch, A., Jia, Y., He, K.: · 2017
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Densely connected convolutional networks
Huang, G., Liu, Z., Weinberger, K., van der Maaten, L.: · 2017
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Learning features by watching objects move
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Learning transferable architectures for scalable image recognition
Zoph, B., Vasudevan, V., Shlens, J., Le, Q.: · 2017
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Storck, P., Cisse, M.: · 2017
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Feature pyramid networks for object detection
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Learning visual n-grams from web data
Li, A., Jabri, A., Joulin, A., van der Maaten, L.: · 2017
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Separating self-expression and visual content in hashtag supervision
Veit, A., Nickel, M., Belongie, S., van der Maaten, L.: · 2017
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Hard mixtures of experts for large scale weakly supervised vision
Gross, S., Ranzato, M., Szlam, A.: · 2017
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Billion-scale similarity search with GPUs
Johnson, J., Douze, M., Jégou, H.: · 2017
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Chen, Y., Li, J., Xiao, H., Jin, X., Yan, S., Feng, J.: · 2017
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Squeeze-and-excitation networks
Hu, J., Shen, L., Sun, G.: · 2017
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Detectron
Girshick, R., Radosavovic, I., Gkioxari, G., Dollár, P., He, K.: · 2018
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