/Meta-Learning-PaperReading

Notes for daily reading papers

Meta-Learning-PaperReading

Notes for daily reading papers

Have Read

No. Abb. title pdf code Brief
1. MTL Meta-Transfer Learning for Few-Shot Learning CVPR 2019 Pytorch Meta-learning; classification
2. ACE ACE: Adapting to Changing Environments for Semantic Segmentation ICCV 2019 No DA; Meta-learning;Lifelong Learning; Segmentation
3. IADA Incremental Adversarial Domain Adaptation for Continually Changing Environments ICRA 2018 Pytorch DA; segmentation
4. ADDA-REPLAY Adapting To Continuously Shifting Domains ICLR Workshop 2018 No DA; classification
5. CANet CANet: Class-Agnostic Segmentation Networks with Iterative Refinement and Attentive Few-Shot Learning CVPR 2019 No few-shot; segmentation

Unread

No. Abb. title pdf code Brief
1. SPNet Semantic Projection Network for Zero- and Few-Label Semantic Segmentation CVPR 2019 Pytorch zero- and few-shot; segmentation
2. MAML Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks ICML 2017 Pytorch Meta-learning; classification
3. OML Online Meta-Learning ICML 2019 No Online; Meta-learning; classification
4. Meta-Sim Meta-Sim: Learning to Generate Synthetic Datasets ICCV 2019 Oral Empty Generalization
5. OMLA Online Adaptation through Meta-Learning for Stereo Depth Estimation ArXiv No Generalization
6. Reptile On First-Order Meta-Learning Algorithms CoRR 2018 No Meta-Learning
7. CMA Continuous Manifold Based Adaptation for Evolving Visual Domains CVPR 2014 Matlab Continuous Adaptation
8. Online Domain Adaptation by Exploiting Labeled Features and Pro-active Learning CoDS-COMAD, 2018 No Online Adaptation
9. Generalizing to Unseen Domains via Adversarial Data Augmentation NIPS 2018(camera ready) No Generalizing
10. Zero-Shot Deep Domain Adaptation ECCV 2018 No Zero-shot
11. Meta-learning autoencoders for few-shot prediction No No Few-shot
12. UM-Adapt UM-Adapt: Unsupervised Multi-Task Adaptation Using Adversarial Cross-Task Distillation ICCV, 2019
13. Lifelong Learning for Sentiment Classification No No Lifelong Learning

Few-shot-PaperReading

Have Read

No. Abb. title pdf code Brief

Unread

No. Abb. title pdf code Brief
1. EGNN Edge-Labeling Graph Neural Network for Few-shot Learning CVPR 2019 Oral Pytorch few-shot-learning; classification
2. LaSO Label-Set Operations networks for multi-label few-shot learning CVPR 2019 Oral No few-shot-learning; classification
3. RepMet Representative-based metric learning for classification and few-shot object detection CVPR 2019 Oral No few-shot-learning; detection
4. RFew Shot Adaptive Faster R-CNN CVPR 2019 Oral No few-shot-learning; detection
5. Deep Tree Learning for Zero-shot Face Anti-Spoofing CVPR 2019 Oral No few-shot-learning; face Anti-Proofing
6. Few-Shot Learning with Localization in Realistic Settings CVPR 2019 Oral No few-shot-learning;
7. Doodle to Search: Practical Zero-Shot Sketch-based Image Retrieval CVPR 2019 Oral No few-shot-learning;
8. Zero-Shot Task Transfer CVPR 2019 Oral No few-shot-learning;Task Transfer
9. Generating Classification Weights with Graph Neural Networks for Few-Shot Learning CVPR 2019 Oral No few-shot-learning;Classification
10. Gradient Matching Generative Networks for Zero-Shot Learning CVPR 2019 Oral No few-shot-learning;
11. Learning Inter-pixel Relations for Weakly Supervised Instance Segmentation CVPR 2019 Oral No few-shot-learning; Instance Segmentation
12. Unsupervised Person Image Generation with Semantic Parsing Transformation CVPR 2019 No few-shot-learning;
13. Rethinking Knowledge Graph Propagation for Zero-Shot Learning CVPR 2019 Oral No few-shot-learning;
14. Generative Dual Adversarial Network for Generalized Zero-shot Learning CVPR 2019 No few-shot-learning;
15. Hierarchical Disentanglement of Discriminative Latent Features for Zero-shot Learning CVPR 2019 No few-shot-learning;
16. Spot and Learn: A Maximum-Entropy Image Patch Sampler for Few-Shot Classification CVPR 2019 No few-shot-learning;
17. Large-Scale Few-Shot Learning: Knowledge Transfer with Class Hierarchy CVPR 2019 No few-shot-learning;
18. Generalized Zero- and Few-Shot Learning via Aligned Variational Autoencoders CVPR 2019 No few-shot-learning;
19. Dense Classification and Implanting for Few-shot Learning CVPR 2019 No few-shot-learning;
20. On zero-shot recognition of generic objects CVPR 2019 No few-shot-learning;
21. out-of-distribution detection for generalized zero-shot action recognition CVPR 2019 No few-shot-learning;