SOTAVerified

Self-Supervised Learning

Self-Supervised Learning is proposed for utilizing unlabeled data with the success of supervised learning. Producing a dataset with good labels is expensive, while unlabeled data is being generated all the time. The motivation of Self-Supervised Learning is to make use of the large amount of unlabeled data. The main idea of Self-Supervised Learning is to generate the labels from unlabeled data, according to the structure or characteristics of the data itself, and then train on this unsupervised data in a supervised manner. Self-Supervised Learning is wildly used in representation learning to make a model learn the latent features of the data. This technique is often employed in computer vision, video processing and robot control.

Source: Self-supervised Point Set Local Descriptors for Point Cloud Registration

Image source: LeCun

Papers

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Showing 2901–2950 of 5044 papers

TitleStatusHype
Knowledge Prompts: Injecting World Knowledge into Language Models through Soft Prompts—0
Non-intrusive Load Monitoring based on Self-supervised Learning—0
Grow and Merge: A Unified Framework for Continuous Categories Discovery—0
Dual-distribution discrepancy with self-supervised refinement for anomaly detection in medical imagesCode1
Revisiting Self-Supervised Contrastive Learning for Facial Expression RecognitionCode1
An Investigation into Whitening Loss for Self-supervised LearningCode1
Temporal Feature Alignment in Contrastive Self-Supervised Learning for Human Activity RecognitionCode1
Unsupervised Few-shot Learning via Deep Laplacian Eigenmaps—0
Brief Introduction to Contrastive Learning Pretext Tasks for Visual Representation—0
Effective Self-supervised Pre-training on Low-compute Networks without DistillationCode1
SimPer: Simple Self-Supervised Learning of Periodic TargetsCode1
Automated Graph Self-supervised Learning via Multi-teacher Knowledge Distillation—0
SPICER: Self-Supervised Learning for MRI with Automatic Coil Sensitivity Estimation and Reconstruction—0
Exploring The Role of Mean Teachers in Self-supervised Masked Auto-EncodersCode1
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine LearningCode0
Multi-task Self-supervised Graph Neural Networks Enable Stronger Task GeneralizationCode1
CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representationsCode1
RankMe: Assessing the downstream performance of pretrained self-supervised representations by their rank—0
Granularity-aware Adaptation for Image Retrieval over Multiple Tasks—0
Differentiable Raycasting for Self-supervised Occupancy ForecastingCode1
MTSMAE: Masked Autoencoders for Multivariate Time-Series Forecasting—0
Backdoor Attacks in the Supply Chain of Masked Image Modeling—0
Clean self-supervised MRI reconstruction from noisy, sub-sampled training data with Robust SSDUCode0
A Generative Shape Compositional Framework to Synthesise Populations of Virtual Chimaeras—0
VICRegL: Self-Supervised Learning of Local Visual FeaturesCode2
Improving Label-Deficient Keyword Spotting Through Self-Supervised PretrainingCode1
An attention-based backend allowing efficient fine-tuning of transformer models for speaker verificationCode0
That Sounds Right: Auditory Self-Supervision for Dynamic Robot ManipulationCode0
Self-omics: A Self-supervised Learning Framework for Multi-omics Cancer DataCode0
Attention Distillation: self-supervised vision transformer students need more guidanceCode1
Contrastive Audio-Visual Masked AutoencoderCode2
What shapes the loss landscape of self-supervised learning?—0
Pixel-global Self-supervised Learning with Uncertainty-aware Context Stabilizer—0
Spectral Augmentation for Self-Supervised Learning on GraphsCode1
Ten Years after ImageNet: A 360° Perspective on AI—0
Multimodality Multi-Lead ECG Arrhythmia Classification using Self-Supervised LearningCode1
Match to Win: Analysing Sequences Lengths for Efficient Self-supervised Learning in Speech and Audio—0
Minimalistic Unsupervised Learning with the Sparse Manifold Transform—0
Slimmable Networks for Contrastive Self-supervised LearningCode0
Variance Covariance Regularization Enforces Pairwise Independence in Self-Supervised Representations—0
Domain-aware Self-supervised Pre-training for Label-Efficient Meme Analysis—0
Joint Embedding Self-Supervised Learning in the Kernel Regime—0
Efficient Medical Image Assessment via Self-supervised Learning—0
Graph Soft-Contrastive Learning via Neighborhood Ranking—0
Non-contrastive representation learning for intervals from well logs—0
Masked Multi-Step Multivariate Time Series Forecasting with Future Information—0
Audio Barlow Twins: Self-Supervised Audio Representation LearningCode0
3D Scene Flow Estimation on Pseudo-LiDAR: Bridging the Gap on Estimating Point Motion—0
End-to-End Lyrics Recognition with Self-supervised Learning—0
The Efficacy of Self-Supervised Speech Models for Audio RepresentationsCode1
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All datasetsDABSSTL-10CIFAR10cifar100ImageNet-100 (TEMI Split)TinyImageNetCIFAR-10CIFAR-100CREMA-DTiny ImageNet

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Pretraining: NoneImages & Text57.5—Unverified
2Pretraining: ShEDImages & Text54.3—Unverified
3Pretraining: e-MixImages & Text48.9—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50Accuracy91.7—Unverified
2ResNet18Accuracy91.02—Unverified
3MV-MRAccuracy89.67—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy93.89—Unverified
2ResNet18average top-1 classification accuracy92.58—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy72.51—Unverified
2ResNet18average top-1 classification accuracy69.31—Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet50)Top-1 Accuracy82.64—Unverified
2CorInfomax (ResNet18)Top-1 Accuracy80.48—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy51.84—Unverified
2ResNet18average top-1 classification accuracy51.67—Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet18)Top-1 Accuracy93.18—Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet18)Top-1 Accuracy71.61—Unverified
#ModelMetricClaimedVerifiedStatus
1Hybrid BYOL-S/CvTAccuracy67.2—Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet50)Top-1 Accuracy54.86—Unverified