No 1. 《A Survey on Contextual Embeddings》
    No 2. 《Metric learning: cross-entropy vs. pairwise losses》
    No 3. 《Meta Pseudo Labels》
    No 4. 《SOLOv2: Dynamic, Faster and Stronger》
    No 5. 《Rethinking Few-Shot Image Classification: a Good Embedding Is All You Need?》
    No 6. 《Do CNNs Encode Data Augmentations?》
    No 7. 《ProGraML: Graph-based Deep Learning for Program Optimization and Analysis》
    No 8. 《TF-IDFC-RF: A Novel Supervised Term Weighting Scheme》
    No 9. 《ASLFeat: Learning Local Features of Accurate Shape and Localization》
    No 10. 《A Survey of Methods for Low-Power Deep Learning and Computer Vision》
    No 11. 《COVID-Net: A Tailored Deep Convolutional Neural Network Design for Detection of COVID-19 Cases from Chest Radiography Images》
    No 12. 《Pre-trained Models for Natural Language Processing: A Survey》
    No 13. 《An End-to-end Framework For Low-Resolution Remote Sensing Semantic Segmentation》
    No 14. 《Atlas: End-to-End 3D Scene Reconstruction from Posed Images》
    No 15. 《Deformable Style Transfer》
    No 16. 《End-to-End Learning Local Multi-view Descriptors for 3D Point Clouds》
    No 17. 《High Accuracy Face Geometry Capture using a Smartphone Video》
    No 18. 《CPS: Class-level 6D Pose and Shape Estimation From Monocular Images》
    No 19. 《GAN Compression: Efficient Architectures for Interactive Conditional GANs》
    No 20. 《Collaborative Distillation for Ultra-Resolution Universal Style Transfer》
    No 21. 《Deep Line Art Video Colorization with a Few References》
    No 22. 《Fixing the train-test resolution discrepancy: FixEfficientNet》
    No 23. 《Weighted Meta-Learning》
    No 24. 《Neural Networks are Surprisingly Modular》
    No 25. 《Calibration of Pre-trained Transformers》
    No 26. 《MINT: Deep Network Compression via Mutual Information-based Neuron Trimming》
    No 27. 《Overinterpretation reveals image classification model pathologies》
    No 28. 《High-Resolution Daytime Translation Without Domain Labels》
    No 29. 《Neural Contours: Learning to Draw Lines from 3D Shapes》
    No 30. 《Self-Supervised Contextual Bandits in Computer Vision》