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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4351–4400 of 5044 papers

TitleStatusHype
BEST-STD: Bidirectional Mamba-Enhanced Speech Tokenization for Spoken Term DetectionCode0
RPT: Toward Transferable Model on Heterogeneous Researcher Data via Pre-TrainingCode0
An Information Criterion for Controlled Disentanglement of Multimodal DataCode0
For self-supervised learning, Rationality implies generalization, provablyCode0
Forensic Histopathological Recognition via a Context-Aware MIL Network Powered by Self-Supervised Contrastive LearningCode0
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised LearningCode0
Perturbed Self-Distillation: Weakly Supervised Large-Scale Point Cloud Semantic SegmentationCode0
T-MAE: Temporal Masked Autoencoders for Point Cloud Representation LearningCode0
Focus on the Positives: Self-Supervised Learning for Biodiversity MonitoringCode0
FLGuard: Byzantine-Robust Federated Learning via Ensemble of Contrastive ModelsCode0
Unified Mask Embedding and Correspondence Learning for Self-Supervised Video SegmentationCode0
An Experimental Comparison Of Multi-view Self-supervised Methods For Music TaggingCode0
PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble TechniquesCode0
Video Representation Learning by Dense Predictive CodingCode0
PECoP: Parameter Efficient Continual Pretraining for Action Quality AssessmentCode0
PatchRot: A Self-Supervised Technique for Training Vision TransformersCode0
PARTICLE: Part Discovery and Contrastive Learning for Fine-grained RecognitionCode0
Benchmarking Self-Supervised Learning Methods for Accelerated MRI ReconstructionCode0
Overcoming Dimensional Collapse in Self-supervised Contrastive Learning for Medical Image SegmentationCode0
SAFE: a SAR Feature Extractor based on self-supervised learning and masked Siamese ViTsCode0
Optimizing the Noise in Self-Supervised Learning: from Importance Sampling to Noise-Contrastive EstimationCode0
SafePowerGraph: Safety-aware Evaluation of Graph Neural Networks for Transmission Power GridsCode0
Optimizing Speech Multi-View Feature Fusion through Conditional ComputationCode0
Fitting a Directional Microstructure Model to Diffusion-Relaxation MRI Data with Self-Supervised Machine LearningCode0
Fine-tuning Strategies for Faster Inference using Speech Self-Supervised Models: A Comparative StudyCode0
Compound Figure Separation of Biomedical Images with Side LossCode0
NeuroMixGDP: A Neural Collapse-Inspired Random Mixup for Private Data ReleaseCode0
Topo2vec: Topography Embedding Using the Fractal EffectCode0
SimSAM: Simple Siamese Representations Based Semantic Affinity Matrix for Unsupervised Image SegmentationCode0
Topology-Aware Modeling for Unsupervised Simulation-to-Reality Point Cloud RecognitionCode0
Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand HygieneCode0
Optimizing Likelihood-free Inference using Self-supervised Neural Symmetry EmbeddingsCode0
Comparing Self-Supervised Learning Models Pre-Trained on Human Speech and Animal Vocalizations for Bioacoustics ProcessingCode0
Operational Latent SpacesCode0
Simulation of Brain Resection for Cavity Segmentation Using Self-Supervised and Semi-Supervised LearningCode0
ToThePoint: Efficient Contrastive Learning of 3D Point Clouds via RecyclingCode0
SAS: Self-Augmentation Strategy for Language Model Pre-trainingCode0
Companion Animal Disease Diagnostics based on Literal-aware Medical Knowledge Graph Representation LearningCode0
Open-source framework for detecting bias and overfitting for large pathology imagesCode0
Clean self-supervised MRI reconstruction from noisy, sub-sampled training data with Robust SSDUCode0
Few-Max: Few-Shot Domain Adaptation for Unsupervised Contrastive Representation LearningCode0
CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge DistillationCode0
Wireless Link Scheduling via Graph Representation Learning: A Comparative Study of Different Supervision LevelsCode0
Scalable Label-efficient Footpath Network Generation Using Remote Sensing Data and Self-supervised LearningCode0
Benchmarking Self-Supervised Contrastive Learning Methods for Image-Based Plant PhenotypingCode0
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly DetectionCode0
Scale dependant layer for self-supervised nuclei encodingCode0
On the Transferability of Visual Features in Generalized Zero-Shot LearningCode0
Scale-Translation Equivariant Network for Oceanic Internal Solitary Wave LocalizationCode0
Benchmarking Robust Self-Supervised Learning Across Diverse Downstream TasksCode0
Show:102550
← PrevPage 88 of 101Next →
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