Unsupervised Learning of Visual Representations Using Videos

ImageNet classification with deep convolutional neural networks

Krizhevsky, A., Sutskever, I., & Hinton, G. E. (2017) · Communications of the ACM · doi:10.1145/3065386 · Cited by 112,155 · see citing works

Distinctive Image Features from Scale-Invariant Keypoints

Lowe, D. G. (2004) · International Journal of Computer Vision · doi:10.1023/b:visi.0000029664.99615.94 · Cited by 55,589 · see citing works

Histograms of Oriented Gradients for Human Detection

Dalal, N., & Triggs, B. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.177 · Cited by 33,584 · see citing works

Rich Feature Hierarchies for Accurate Object Detection and Semantic Segmentation

Girshick, R., Donahue, J., Darrell, T., & Malik, J. (2014) · 2014 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2014.81 · Cited by 32,684 · see citing works

Reducing the dimensionality of data with neural networks

Hinton, G. E., & Salakhutdinov, R. R. (2006) · Science · doi:10.1126/science.1127647 · Cited by 20,928 · see citing works

The pascal visual object classes (VOC) challenge

Everingham, M., Van Gool, L., Williams, C. K. I., Winn, J., & Zisserman, A. (2010) · International Journal of Computer Vision · doi:10.1007/s11263-009-0275-4 · Cited by 19,599 · see citing works

SURF: Speeded Up Robust Features

Bay, H., Tuytelaars, T., & Van Gool, L. (2006) · Lecture Notes in Computer Science · doi:10.1007/11744023_32 · Cited by 14,955 · see citing works

Representation Learning: A Review and New Perspectives

Bengio, Y., Courville, A., & Vincent, P. (2013) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2013.50 · Cited by 13,001 · see citing works

Caffe: Convolutional Architecture for Fast Feature Embedding

Jia, Y., Shelhamer, E., Donahue, J., Karayev, S., Long, J., Girshick, R., Guadarrama, S., & Darrell, T. (2014) · Proceedings of the 22nd ACM international conference on Multimedia · doi:10.1145/2647868.2654889 · Cited by 11,077 · see citing works

Extracting and composing robust features with denoising autoencoders

Vincent, P., Larochelle, H., Bengio, Y., & Manzagol, P.-A. (2008) · Proceedings of the 25th international conference on Machine learning - ICML '08 · doi:10.1145/1390156.1390294 · Cited by 7,436 · see citing works

Indoor segmentation and support inference from rgbd images

Silberman, N., Hoiem, D., Kohli, P., & Fergus, R. (2012) · Lecture Notes in Computer Science · doi:10.1007/978-3-642-33715-4_54 · Cited by 5,760 · see citing works

High-Speed Tracking with Kernelized Correlation Filters

Henriques, J. F., Caseiro, R., Martins, P., & Batista, J. (2015) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2014.2345390 · Cited by 5,753 · see citing works

Dimensionality Reduction by Learning an Invariant Mapping

Hadsell, R., Chopra, S., & LeCun, Y. (2006) · 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2 (CVPR'06) · doi:10.1109/cvpr.2006.100 · Cited by 5,336 · see citing works

Greedy layer-wise training of deep networks

Bengio, Y., Lamblin, P., Popovici, D., & Larochelle, H. (2007) · Advances in Neural Information Processing Systems 19 · doi:10.7551/mitpress/7503.003.0024 · Cited by 4,841 · see citing works

Learning a Similarity Metric Discriminatively, with Application to Face Verification

Chopra, S., Hadsell, R., & LeCun, Y. (2005) · 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) · doi:10.1109/cvpr.2005.202 · Cited by 4,036 · see citing works

Untitled work

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Sparse coding with an overcomplete basis set: A strategy employed by V1?

Olshausen, B. A., & Field, D. J. (1997) · Vision Research · doi:10.1016/s0042-6989(97)00169-7 · Cited by 3,642 · see citing works

Action Recognition with Improved Trajectories

Wang, H., & Schmid, C. (2013) · 2013 IEEE International Conference on Computer Vision · doi:10.1109/iccv.2013.441 · Cited by 3,407 · see citing works

Unsupervised Visual Representation Learning by Context Prediction

Doersch, C., Gupta, A., & Efros, A. A. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.167 · Cited by 2,629 · see citing works

Convolutional deep belief networks for scalable unsupervised learning of hierarchical representations

Lee, H., Grosse, R., Ranganath, R., & Ng, A. Y. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553453 · Cited by 2,412 · see citing works

Deep Metric Learning Using Triplet Network

Hoffer, E., & Ailon, N. (2015) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-24261-3_7 · Cited by 2,134 · see citing works

Unsupervised Learning of Video Representations using LSTMs

Srivastava, N., Mansimov, E., & Salakhutdinov, R. (2015) · arXiv · doi:10.48550/arxiv.1502.04681 · Cited by 1,861 · see citing works

Building high-level features using large scale unsupervised learning

Le, Q. V. (2013) · 2013 IEEE International Conference on Acoustics, Speech and Signal Processing · doi:10.1109/icassp.2013.6639343 · Cited by 1,695 · see citing works

Recognizing indoor scenes

Quattoni, A., & Torralba, A. B. (2009) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2009.5206537 · Cited by 1,533 · see citing works

Slow Feature Analysis: Unsupervised Learning of Invariances

Wiskott, L., & B, T. J. S. A. (2002) · Neural Computation · doi:10.1162/089976602317318938 · Cited by 1,351 · see citing works

Learning Fine-Grained Image Similarity with Deep Ranking

Wang, J., Song, Y., Leung, T., Rosenberg, C., Wang, J., Philbin, J. F., Chen, B., & Wu, Y. N. (2014) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2014.180 · Cited by 1,282 · see citing works

Unsupervised Learning of Invariant Feature Hierarchies with Applications to Object Recognition

Ranzato, M., Huang, F., Boureau, Y.-L., & LeCun, Y. (2007) · 2007 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2007.383157 · Cited by 1,186 · see citing works

The "Wake-Sleep" Algorithm for Unsupervised Neural Networks

Hinton, G. E., Dayan, P., Frey, B. J., & Neal, R. M. (1995) · Science · doi:10.1126/science.7761831 · Cited by 1,070 · see citing works

Multimodal Learning with Deep Boltzmann Machines

Srivastava, N., & Salakhutdinov, R. (2012) · doi:10.5555/2627435.2697059 · Cited by 1,070 · see citing works

Discovering objects and their location in images

Šivic, J., Russell, B. C., Efros, A. A., Zisserman, A., & Freeman, W. T. (2005) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2005.77 · Cited by 973 · see citing works

Learning hierarchical invariant spatio-temporal features for action recognition with independent subspace analysis

Le, Q. V., Zou, W. Y., Yeung, S. Y., & Ng, A. Y. (2011) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2011.5995496 · Cited by 966 · see citing works

Pedestrian Detection with Unsupervised Multi-stage Feature Learning

Sermanet, P., Kavukcuoglu, K., Chintala, S., & LeCun, Y. (2013) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2013.465 · Cited by 753 · see citing works

Learning invariance from transformation sequences

Földiák, P. (1991) · Neural Computation · doi:10.1162/neco.1991.3.2.194 · Cited by 661 · cited 1× · see citing works

Convolutional Learning of Spatio-temporal Features

Taylor, G. W., Fergus, R., LeCun, Y., & Bregler, C. (2010) · Lecture notes in computer science · doi:10.1007/978-3-642-15567-3_11 · Cited by 645 · see citing works

Building high-level features using large scale unsupervised learning

Ranzato, M., Monga, R., Devin, M., Chen, K., Corrado, G. S., Dean, J., Le, Q. V., & Ng, A. Y. (2012) · International Conference on Machine Learning · Cited by 633 · see citing works

Using Multiple Segmentations to Discover Objects and their Extent in Image Collections

Russell, B. C., Freeman, W. T., Efros, A. A., Šivic, J., & Zisserman, A. (2006) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2006.326 · Cited by 612 · see citing works

Unsupervised Discovery of Mid-Level Discriminative Patches

Singh, S., Gupta, A., & Efros, A. A. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33709-3_6 · Cited by 517 · see citing works

Bit-Scalable Deep Hashing With Regularized Similarity Learning for Image Retrieval and Person Re-Identification

Zhang, R., Lin, L., Zhang, R., Zuo, W., & Lei Zhang, A. (2015) · IEEE Transactions on Image Processing · doi:10.1109/tip.2015.2467315 · Cited by 504 · see citing works

Learning descriptors for object recognition and 3D pose estimation

Wohlhart, P., & Lepetit, V. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298930 · Cited by 452 · see citing works

Designing deep networks for surface normal estimation

Wang, X., Fouhey, D. F., & Gupta, A. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298652 · Cited by 343 · see citing works

Deep learning from temporal coherence in video

Mobahi, H., Collobert, R., & Weston, J. (2009) · Proceedings of the 26th Annual International Conference on Machine Learning · doi:10.1145/1553374.1553469 · Cited by 328 · see citing works

Deep Convolutional Ranking for Multilabel Image AnnotationPreprint

Gong, Y., Jia, Y., Leung, T., Toshev, A., & Ioffe, S. (2014) · Cited by 272 · see citing works

Discriminative Decorrelation for Clustering and Classification

Hariharan, B., Malik, J., & Ramanan, D. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-33765-9_33 · Cited by 271 · see citing works

Mid-level Visual Element Discovery as Discriminative Mode Seeking

Doersch, C., Gupta, A., & Efros, A. A. (2013) · neural information processing systems · Cited by 238 · see citing works

Hierarchical face parsing via deep learning

Luo, P., Wang, X., & Tang, X. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247963 · Cited by 190 · see citing works

Robust Boltzmann Machines for recognition and denoising

Tang, Y., Salakhutdinov, R., & Hinton, G. E. (2012) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2012.6247936 · Cited by 171 · see citing works

Data-Driven 3D Primitives for Single Image Understanding

Fouhey, D. F., Gupta, A., & Hebert, M. (2013) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2013.421 · Cited by 167 · see citing works

Unsupervised Learning of Spatiotemporally Coherent Metrics

Goroshin, R., Bruna, J., Tompson, J., Eigen, D., & LeCun, Y. (2015) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.465 · Cited by 156 · see citing works

Matching-CNN meets KNN: Quasi-parametric human parsing

Liu, S., Liang, X., Liu, L., Shen, X., Yang, J., Xu, C., Lin, L., Cao, X., & Yan, S. (2015) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2015.7298748 · Cited by 142 · see citing works

Deep Learning of Invariant Features via Simulated Fixations in Video

Zou, W. Y., Shenghuo Zhu, B., Yu, K., & Ng, A. Y. (2012) · Cited by 131 · see citing works

Describing Visual Scenes using Transformed Dirichlet Processes

Torralba, A. B., Willsky, A. S., Sudderth, E. B., & Freeman, W. T. (2005) · neural information processing systems · Cited by 122 · see citing works

Discriminatively Trained Dense Surface Normal Estimation

Ladický, Ľ., Zeisl, B., & Pollefeys, M. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10602-1_31 · Cited by 120 · see citing works

Unfolding an Indoor Origami World

Fouhey, D. F., Gupta, A., & Hebert, M. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10599-4_44 · Cited by 85 · see citing works

The Shape Boltzmann Machine: A strong model of object shape

Eslami, S. M. A., Heess, N., & Winn, J. (2012) · 2012 IEEE Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2012.6247702 · Cited by 61 · see citing works

Context as Supervisory Signal: Discovering Objects with Predictable Context

Doersch, C., Gupta, A., & Efros, A. A. (2014) · Lecture notes in computer science · doi:10.1007/978-3-319-10578-9_24 · Cited by 39 · see citing works

Unsupervised learning of invariant features using video

Stavens, D., & Thrun, S. (2010) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2010.5539773 · Cited by 36 · see citing works

Computational Baby LearningPreprint

Liang, X., Liu, S., Wei, Y., Liu, L., Lin, L., & Yan, S. (2014) · arXiv (Cornell University) · doi:10.48550/arxiv.1411.2861 · Cited by 17 · see citing works

The Unreasonable Effectiveness of Deep Features as a Perceptual Metric

Zhang, R., Isola, P., Efros, A. A., Shechtman, E., & Wang, O. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00068 · Cited by 14,623 · see citing works

Momentum Contrast for Unsupervised Visual Representation Learning

He, K., Fan, H., Wu, Y., Xie, S., & Girshick, R. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00975 · Cited by 13,347 · see citing works

Masked Autoencoders Are Scalable Vision Learners

He, K., Chen, X., Xie, S., Li, Y., Dollar, P., & Girshick, R. (2022) · 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr52688.2022.01553 · Cited by 8,489 · see citing works

Representation Learning with Contrastive Predictive Coding

Oord, A. V. D., Li, Y., & Vinyals, O. (2018) · arXiv · doi:10.48550/arxiv.1807.03748 · Cited by 6,242 · see citing works

Context Encoders: Feature Learning by Inpainting

Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., & Efros, A. A. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.278 · Cited by 5,691 · see citing works

Unsupervised Feature Learning via Non-parametric Instance Discrimination

Wu, Z., Xiong, Y., Yu, S. X., & Lin, D. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00393 · Cited by 3,664 · see citing works

Colorful Image Colorization

Zhang, R., Isola, P., & Efros, A. A. (2016) · European Conference on Computer Vision · doi:10.1007/978-3-319-46487-9_40 · Cited by 3,803 · see citing works

Unsupervised Learning of Depth and Ego-Motion from Video

Zhou, T., Brown, M., Snavely, N., & Lowe, D. G. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.700 · Cited by 2,910 · see citing works

Unsupervised Learning of Visual Representations by Solving Jigsaw Puzzles

Noroozi, M., & Favaro, P. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46466-4_5 · Cited by 2,775 · see citing works

Training Region-Based Object Detectors with Online Hard Example Mining

Shrivastava, A., Gupta, A., & Girshick, R. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.89 · Cited by 2,686 · see citing works

Unsupervised Visual Representation Learning by Context Prediction

Doersch, C., Gupta, A., & Efros, A. A. (2015) · 2015 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2015.167 · Cited by 2,629 · see citing works

Deep Clustering for Unsupervised Learning of Visual Features

Caron, M., Bojanowski, P., Joulin, A., & Douze, M. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01264-9_9 · Cited by 2,674 · see citing works

Revisiting Unreasonable Effectiveness of Data in Deep Learning Era

Sun, C., Shrivastava, A., Singh, S., & Gupta, A. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.97 · Cited by 2,484 · see citing works

Self-Supervised Visual Feature Learning With Deep Neural Networks: A Survey

Jing, L., & Tian, Y. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2020.2992393 · Cited by 2,036 · see citing works

Contrastive Multiview Coding

Tian, Y., Krishnan, D., & Isola, P. (2020) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-58621-8_45 · Cited by 1,997 · see citing works

ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Clark, K., Luong, M.-T., Le, Q. V., & Manning, C. D. (2020) · arXiv · doi:10.48550/arxiv.2003.10555 · Cited by 1,844 · see citing works

GOT-10k: A Large High-Diversity Benchmark for Generic Object Tracking in the Wild

Huang, L., Zhao, X., & Huang, K. (2021) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2019.2957464 · Cited by 1,809 · see citing works

Curiosity-Driven Exploration by Self-Supervised Prediction

Pathak, D., Agrawal, P., Efros, A. A., & Darrell, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) · doi:10.1109/cvprw.2017.70 · Cited by 1,815 · see citing works

Self-Supervised Learning of Pretext-Invariant Representations

Misra, I., & van der Maaten, L. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr42600.2020.00674 · Cited by 1,435 · see citing works

Network Dissection: Quantifying Interpretability of Deep Visual Representations

Bau, D., Zhou, B., Khosla, A., Oliva, A., & Torralba, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.354 · Cited by 1,389 · see citing works

Adversarial Feature LearningPreprint

Donahue, J., Krähenbühl, P., & Darrell, T. (2016) · International Conference on Learning Representations · doi:10.48550/arxiv.1605.09782 · Cited by 1,982 · see citing works

Rethinking ImageNet Pre-Training

He, K., Girshick, R., & Dollár, P. (2019) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2019.00502 · Cited by 1,164 · see citing works

Taskonomy: Disentangling Task Transfer Learning

Zamir, A. R., Sax, A., Shen, W., Guibas, L., Malik, J., & Savarese, S. (2018) · 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2018.00391 · Cited by 1,128 · see citing works

Data-Efficient Image Recognition with Contrastive Predictive Coding

Hénaff, O. J., Srinivas, A., De Fauw, J., Razavi, A., Doersch, C., Eslami, S. M. A., & Oord, A. V. D. (2019) · arXiv · doi:10.48550/arxiv.1905.09272 · Cited by 1,014 · see citing works

Generating Videos with Scene DynamicsPreprint

Vondrick, C., Pirsiavash, H., & Torralba, A. B. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1609.02612 · Cited by 976 · see citing works

Contrastive Representation Learning: A Framework and Review

Le-Khac, P. H., Healy, G., & Smeaton, A. F. (2020) · IEEE Access · doi:10.1109/access.2020.3031549 · Cited by 862 · see citing works

Domain Generalization by Solving Jigsaw Puzzles

Carlucci, F. M., D’Innocente, A., Bucci, S., Barbara Caputo, B., & Tommasi, T. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00233 · Cited by 838 · see citing works

Look, Listen and Learn

Arandjelović, R., & Zisserman, A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.73 · Cited by 836 · see citing works

Joint Unsupervised Learning of Deep Representations and Image Clusters

Yang, J., Parikh, D., & Batra, D. (2016) · 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2016.556 · Cited by 879 · see citing works

Human Action Recognition and Prediction: A Survey

Kong, Y., & Fu, Y. (2022) · International Journal of Computer Vision · doi:10.1007/s11263-022-01594-9 · Cited by 832 · see citing works

Shuffle and Learn: Unsupervised Learning Using Temporal Order Verification

Misra, I., Zitnick, C. L., & Hebert, M. (2016) · Lecture Notes in Computer Science · doi:10.1007/978-3-319-46448-0_32 · Cited by 779 · see citing works

Video Frame Synthesis Using Deep Voxel Flow

Liu, Z., Yeh, R. A., Tang, X., Liu, Y., & Agarwala, A. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.478 · Cited by 766 · see citing works

Audio-Visual Scene Analysis with Self-Supervised Multisensory Features

Owens, A., & Efros, A. A. (2018) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-01231-1_39 · Cited by 704 · see citing works

Deep Predictive Coding Networks for Video Prediction and Unsupervised LearningPreprint

Lotter, W. E., Kreiman, G., & Cox, D. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1605.08104 · Cited by 805 · see citing works

A-Fast-RCNN: Hard Positive Generation via Adversary for Object Detection

Wang, X., Shrivastava, A., & Gupta, A. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.324 · Cited by 655 · see citing works

Going deeper into action recognition: A survey

Herath, S., Harandi, M. T., & Porikli, F. (2017) · Image and Vision Computing · doi:10.1016/j.imavis.2017.01.010 · Cited by 646 · see citing works

Split-Brain Autoencoders: Unsupervised Learning by Cross-Channel Prediction

Zhang, R., Isola, P., & Efros, A. A. (2016) · Computer Vision and Pattern Recognition · doi:10.1109/cvpr.2017.76 · Cited by 724 · see citing works

Unsupervised Embedding Learning via Invariant and Spreading Instance Feature

Ye, M., Zhang, X., Yuen, P. C., & Chang, S. (2019) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2019.00637 · Cited by 629 · see citing works

End-to-End Learning of Visual Representations From Uncurated Instructional Videos

Miech, A., Alayrac, J.-B., Smaira, L., Laptev, I., Šivic, J., & Zisserman, A. (2020) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr42600.2020.00990 · Cited by 622 · see citing works

Multi-task Self-Supervised Visual Learning

Doersch, C., & Zisserman, A. (2017) · IEEE International Conference on Computer Vision · doi:10.1109/iccv.2017.226 · Cited by 682 · see citing works

Generative Image Modeling Using Style and Structure Adversarial Networks

Wang, X., & Gupta, A. (2016) · Lecture notes in computer science · doi:10.1007/978-3-319-46493-0_20 · Cited by 607 · see citing works

Self-supervised learning for medical image analysis using image context restoration

Chen, L., Bentley, P., Mori, K., Misawa, K., Fujiwara, M., & Rueckert, D. (2019) · Medical Image Analysis · doi:10.1016/j.media.2019.101539 · Cited by 575 · see citing works

Time-Contrastive Networks: Self-Supervised Learning from Video

Sermanet, P., Lynch, C., Chebotar, Y., Hsu, J., Jang, E., Stefan Schaal, A., Levine, S., & Brain, G. (2018) · Proceedings - IEEE International Conference on Robotics and Automation/Proceedings · doi:10.1109/icra.2018.8462891 · Cited by 579 · see citing works

A comprehensive survey on pretrained foundation models: a history from BERT to ChatGPT

Zhou, C., Li, Q., Li, C., Yu, J., Liu, Y., Wang, G., Zhang, K., Ji, C., Yan, Q., He, L., et al. (2024) · International Journal of Machine Learning and Cybernetics · doi:10.1007/s13042-024-02443-6 · Cited by 704 · see citing works

Few-Shot Image Recognition by Predicting Parameters from Activations

Qiao, S., Liu, C., Shen, W., & Yuille, A. (2018) · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · doi:10.1109/cvpr.2018.00755 · Cited by 565 · see citing works

RankIQA: Learning from Rankings for No-Reference Image Quality Assessment

Liu, X., van de Weijer, J., & Bagdanov, A. D. (2017) · IEEE/CVF International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.118 · Cited by 543 · see citing works

Unsupervised Representation Learning by Sorting Sequences

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Anticipating Visual Representations from Unlabeled Video

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Colorization as a Proxy Task for Visual Understanding

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Representation Learning by Learning to Count

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Self-Supervised Video Representation Learning with Space-Time Cubic Puzzles

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On Mutual Information Maximization for Representation LearningPreprint

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A Review on Deep Learning Techniques for Video Prediction

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Boosting Self-Supervised Learning via Knowledge Transfer

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Self-Supervised Learning by Cross-Modal Audio-Video Clustering

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Localizing and Orienting Street Views Using Overhead Imagery

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Deep Metric Learning via Facility Location

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Geography-Aware Self-Supervised Learning

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Self-Supervised Pretraining of 3D Features on any Point-Cloud

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Blazingly Fast Video Object Segmentation with Pixel-Wise Metric Learning

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Ranked List Loss for Deep Metric Learning

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Multi-object Tracking with Quadruplet Convolutional Neural Networks

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Learning to Learn How to Learn: Self-Adaptive Visual Navigation Using Meta-Learning

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Unsupervised Visual Representation Learning by Context PredictionPreprint

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Self-Taught convolutional neural networks for short text clustering

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Object-Centric Representation Learning from Unlabeled Videos

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Unsupervised Representation Learning with Clustering in Deep Convolutional Networks

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Unsupervised Deep Tracking

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A Classification approach towards Unsupervised Learning of Visual RepresentationsPreprint

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Evolving Losses for Unsupervised Video Representation Learning

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