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Methodology
← Learning Types
Machine Learning
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Learning Types
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Self-Supervised Learning
8255 directly classified papers
Papers per year
2006: 8
2007: 7
2008: 7
2009: 9
2010: 12
2011: 7
2012: 13
2013: 11
2014: 12
2015: 17
2016: 35
2017: 97
2018: 191
2019: 441
2020: 663
2021: 1166
2022: 1170
2023: 1544
2024: 1323
2025: 1205
2026: 317
Papers
Rare Event Detection Using Disentangled Representation Learning
CVPR 2019
Learning for Single-Shot Confidence Calibration in Deep Neural Networks Through Stochastic Inferences
CVPR 2019
Speech2Face: Learning the Face Behind a Voice
CVPR 2019
Self-Supervised Convolutional Subspace Clustering Network
CVPR 2019
Self-Supervised Spatio-Temporal Representation Learning for Videos by Predicting Motion and Appearance Statistics
CVPR 2019
OCGAN: One-Class Novelty Detection Using GANs With Constrained Latent Representations
CVPR 2019
LBS Autoencoder: Self-Supervised Fitting of Articulated Meshes to Point Clouds
CVPR 2019
SOSNet: Second Order Similarity Regularization for Local Descriptor Learning
CVPR 2019
Connecting the Dots: Learning Representations for Active Monocular Depth Estimation
CVPR 2019
Latent Space Autoregression for Novelty Detection
CVPR 2019
Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts
IJCNLP 2019
Monocular 3D Human Pose Estimation by Generation and Ordinal Ranking
ICCV 2019
Scaling and Benchmarking Self-Supervised Visual Representation Learning
ICCV 2019
A Simple Baseline for Audio-Visual Scene-Aware Dialog
CVPR 2019
Self-Supervised GANs via Auxiliary Rotation Loss
CVPR 2019
Where's Wally Now? Deep Generative and Discriminative Embeddings for Novelty Detection
CVPR 2019
Self-Supervised Representation Learning From Videos for Facial Action Unit Detection
CVPR 2019
Self-Supervised 3D Hand Pose Estimation Through Training by Fitting
CVPR 2019
Self-Supervised Spatiotemporal Learning via Video Clip Order Prediction
CVPR 2019
Learning Monocular Depth Estimation Infusing Traditional Stereo Knowledge
CVPR 2019
Refine and Distill: Exploiting Cycle-Inconsistency and Knowledge Distillation for Unsupervised Monocular Depth Estimation
CVPR 2019
Neural-Guided RANSAC: Learning Where to Sample Model Hypotheses
ICCV 2019
Discovering Visual Patterns in Art Collections With Spatially-Consistent Feature Learning
CVPR 2019
Interpretable and Fine-Grained Visual Explanations for Convolutional Neural Networks
CVPR 2019
A Mutual Learning Method for Salient Object Detection With Intertwined Multi-Supervision
CVPR 2019
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