Label Independent Memory for Semi-Supervised Few-Shot Video Classification
暂无分享,去创建一个
Yi Yang | Linchao Zhu | Yi Yang | Linchao Zhu
[1] Sergey Levine,et al. Unsupervised Learning via Meta-Learning , 2018, ICLR.
[2] James Philbin,et al. FaceNet: A unified embedding for face recognition and clustering , 2015, 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[3] Yann LeCun,et al. A Closer Look at Spatiotemporal Convolutions for Action Recognition , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[4] David Berthelot,et al. MixMatch: A Holistic Approach to Semi-Supervised Learning , 2019, NeurIPS.
[5] Yi Yang,et al. Compound Memory Networks for Few-Shot Video Classification , 2018, ECCV.
[6] Cordelia Schmid,et al. Aggregating local descriptors into a compact image representation , 2010, 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.
[7] Bowen Zhou,et al. A Structured Self-attentive Sentence Embedding , 2017, ICLR.
[8] Li Fei-Fei,et al. Every Moment Counts: Dense Detailed Labeling of Actions in Complex Videos , 2015, International Journal of Computer Vision.
[9] Apostol Natsev,et al. YouTube-8M: A Large-Scale Video Classification Benchmark , 2016, ArXiv.
[10] Joshua B. Tenenbaum,et al. One shot learning of simple visual concepts , 2011, CogSci.
[11] Abhinav Gupta,et al. ActionVLAD: Learning Spatio-Temporal Aggregation for Action Classification , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[12] Hongyi Zhang,et al. mixup: Beyond Empirical Risk Minimization , 2017, ICLR.
[13] Fabio Viola,et al. The Kinetics Human Action Video Dataset , 2017, ArXiv.
[14] Joshua B. Tenenbaum,et al. Meta-Learning for Semi-Supervised Few-Shot Classification , 2018, ICLR.
[15] Andrew Zisserman,et al. Two-Stream Convolutional Networks for Action Recognition in Videos , 2014, NIPS.
[16] Lorenzo Torresani,et al. Learning Spatiotemporal Features with 3D Convolutional Networks , 2014, 2015 IEEE International Conference on Computer Vision (ICCV).
[17] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[18] Nikos Komodakis,et al. Dynamic Few-Shot Visual Learning Without Forgetting , 2018, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[19] Yi Yang,et al. Transductive Propagation Network for Few-shot Learning , 2018, ArXiv.
[20] Sergey Levine,et al. Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks , 2017, ICML.
[21] Tao Xiang,et al. Learning to Compare: Relation Network for Few-Shot Learning , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.
[22] Richard S. Zemel,et al. Prototypical Networks for Few-shot Learning , 2017, NIPS.
[23] Bernt Schiele,et al. Learning to Self-Train for Semi-Supervised Few-Shot Classification , 2019, NeurIPS.
[24] Andrew Zisserman,et al. Quo Vadis, Action Recognition? A New Model and the Kinetics Dataset , 2017, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[25] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[26] Pietro Perona,et al. One-shot learning of object categories , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[27] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[28] Aurko Roy,et al. Learning to Remember Rare Events , 2017, ICLR.
[29] Daan Wierstra,et al. Meta-Learning with Memory-Augmented Neural Networks , 2016, ICML.
[30] Chen Sun,et al. Rethinking Spatiotemporal Feature Learning: Speed-Accuracy Trade-offs in Video Classification , 2017, ECCV.
[31] Yuan Yu,et al. TensorFlow: A system for large-scale machine learning , 2016, OSDI.
[32] Jian Sun,et al. Identity Mappings in Deep Residual Networks , 2016, ECCV.
[33] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[34] Trevor Darrell,et al. Sequence to Sequence -- Video to Text , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).
[35] Susanne Westphal,et al. The “Something Something” Video Database for Learning and Evaluating Visual Common Sense , 2017, 2017 IEEE International Conference on Computer Vision (ICCV).
[36] Timo Aila,et al. Temporal Ensembling for Semi-Supervised Learning , 2016, ICLR.
[37] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[38] Ivan Laptev,et al. Learnable pooling with Context Gating for video classification , 2017, ArXiv.
[39] Juan Carlos Niebles,et al. Few-Shot Video Classification via Temporal Alignment , 2019, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Harri Valpola,et al. Weight-averaged consistency targets improve semi-supervised deep learning results , 2017, ArXiv.
[41] Cordelia Schmid,et al. Action Recognition with Improved Trajectories , 2013, 2013 IEEE International Conference on Computer Vision.
[42] Andrew Zisserman,et al. All About VLAD , 2013, 2013 IEEE Conference on Computer Vision and Pattern Recognition.
[43] Jason Weston,et al. Memory Networks , 2014, ICLR.
[44] Yi Yang,et al. ActBERT: Learning Global-Local Video-Text Representations , 2020, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
[45] Oriol Vinyals,et al. Matching Networks for One Shot Learning , 2016, NIPS.
[46] Yi Yang,et al. Bidirectional Multirate Reconstruction for Temporal Modeling in Videos , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[47] Luc Van Gool,et al. Temporal Segment Networks: Towards Good Practices for Deep Action Recognition , 2016, ECCV.
[48] Paul A. Viola,et al. Learning from one example through shared densities on transforms , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).
[49] Sergey Ioffe,et al. Rethinking the Inception Architecture for Computer Vision , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).