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Methodology
← Learning Types
Deep Learning
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Learning Types
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Self-Supervised Learning
2959 directly classified papers
Papers per year
2006: 3
2007: 1
2008: 2
2009: 3
2010: 1
2011: 3
2012: 5
2013: 5
2014: 8
2015: 9
2016: 15
2017: 23
2018: 59
2019: 146
2020: 289
2021: 389
2022: 485
2023: 547
2024: 445
2025: 502
2026: 19
Papers
BoxTeacher: Exploring High-Quality Pseudo Labels for Weakly Supervised Instance Segmentation
CVPR 2023
Q: How To Specialize Large Vision-Language Models to Data-Scarce VQA Tasks? A: Self-Train on Unlabeled Images!
CVPR 2023
Modeling the Distributional Uncertainty for Salient Object Detection Models
CVPR 2023
EVA: Exploring the Limits of Masked Visual Representation Learning at Scale
CVPR 2023
Test-time Adaptation with Slot-Centric Models
ICML 2023
Multisample Flow Matching: Straightening Flows with Minibatch Couplings
ICML 2023
Deep Clustering with Incomplete Noisy Pairwise Annotations: A Geometric Regularization Approach
ICML 2023
PointCMP: Contrastive Mask Prediction for Self-Supervised Learning on Point Cloud Videos
CVPR 2023
Sample and Predict Your Latent: Modality-free Sequential Disentanglement via Contrastive Estimation
ICML 2023
NeuralUDF: Learning Unsigned Distance Fields for Multi-View Reconstruction of Surfaces With Arbitrary Topologies
CVPR 2023
Diffusion Based Representation Learning
ICML 2023
Exposing the Self-Supervised Space-Time Correspondence Learning via Graph Kernels
AAAI 2023
CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations
ICML 2023
Learning Signed Distance Functions from Noisy 3D Point Clouds via Noise to Noise Mapping
ICML 2023
Sound to Visual Scene Generation by Audio-to-Visual Latent Alignment
CVPR 2023
Dink-Net: Neural Clustering on Large Graphs
ICML 2023
Fully Self-Supervised Depth Estimation From Defocus Clue
CVPR 2023
Learning With Noisy Labels via Self-Supervised Adversarial Noisy Masking
CVPR 2023
PATS: Patch Area Transportation With Subdivision for Local Feature Matching
CVPR 2023
Architecture-Agnostic Masked Image Modeling -- From ViT back to CNN
ICML 2023
Generalization Analysis for Contrastive Representation Learning
ICML 2023
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning
ICML 2023
DPE: Disentanglement of Pose and Expression for General Video Portrait Editing
CVPR 2023
DISC: Learning From Noisy Labels via Dynamic Instance-Specific Selection and Correction
CVPR 2023
Tied-Augment: Controlling Representation Similarity Improves Data Augmentation
ICML 2023
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