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![]() High-order structure preserving graph neural network for few-shot
learningIEEE Internet of Things Journal (IEEE IoT J.), 2020 |
![]() Boosting Few-Shot Learning With Adaptive Margin LossComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() OSLNet: Deep Small-Sample Classification with an Orthogonal Softmax
LayerIEEE Transactions on Image Processing (TIP), 2020 |
![]() Meta-Learning in Neural Networks: A SurveyIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 |
![]() Learning to Segment the TailComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() Self-Augmentation: Generalizing Deep Networks to Unseen Classes for
Few-Shot LearningNeural Networks (NN), 2020 |
![]() DPGN: Distribution Propagation Graph Network for Few-shot LearningComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() MetaFuse: A Pre-trained Fusion Model for Human Pose EstimationComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() Domain-Adaptive Few-Shot LearningIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 |
![]() Learning Meta Face Recognition in Unseen DomainsComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() DeepEMD: Differentiable Earth Mover's Distance for Few-Shot LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 |
![]() Incremental Few-Shot Object DetectionComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot LearningIEEE International Conference on Computer Vision (ICCV), 2020 |
![]() Embedding Propagation: Smoother Manifold for Few-Shot ClassificationEuropean Conference on Computer Vision (ECCV), 2020 |
![]() MatchingGAN: Matching-based Few-shot Image GenerationIEEE International Conference on Multimedia and Expo (ICME), 2020 |
![]() LEEP: A New Measure to Evaluate Transferability of Learned
RepresentationsInternational Conference on Machine Learning (ICML), 2020 |
![]() Meta-Transfer Learning for Zero-Shot Super-ResolutionComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() Mnemonics Training: Multi-Class Incremental Learning without ForgettingComputer Vision and Pattern Recognition (CVPR), 2020 |
![]() GradMix: Multi-source Transfer across Domains and TasksIEEE Workshop/Winter Conference on Applications of Computer Vision (WACV), 2020 |
Few-Shot Learning as Domain Adaptation: Algorithm and AnalysisInternational Conference on Machine Learning (ICML), 2020 |
![]() Crowdsourcing the Perception of Machine TeachingInternational Conference on Human Factors in Computing Systems (CHI), 2020 |
![]() Fast Adaptation to Super-Resolution Networks via Meta-LearningEuropean Conference on Computer Vision (ECCV), 2020 |
![]() FDFtNet: Facing Off Fake Images using Fake Detection Fine-tuning NetworkIFIP International Information Security Conference (IIS), 2020 |
![]() Associative Alignment for Few-shot Image ClassificationEuropean Conference on Computer Vision (ECCV), 2019 |
![]() A Two-Stage Approach to Few-Shot Learning for Image RecognitionIEEE Transactions on Image Processing (TIP), 2019 |
![]() Learning Multi-level Weight-centric Features for Few-shot LearningPattern Recognition (Pattern Recognit.), 2019 |
![]() Defensive Few-shot LearningIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2019 |
![]() Self-Supervised Learning For Few-Shot Image ClassificationIEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), 2019 |
![]() Learning to Customize Model Structures for Few-shot Dialogue Generation
TasksAnnual Meeting of the Association for Computational Linguistics (ACL), 2019 |