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 4951–5000 of 5044 papers

TitleStatusHype
Self-supervised Representation Learning for Evolutionary Neural Architecture SearchCode0
How Well Do Unsupervised Learning Algorithms Model Human Real-time and Life-long Learning?Code0
Self-Supervised Representation Learning From Videos for Facial Action Unit DetectionCode0
STRIDE: Single-video based Temporally Continuous Occlusion-Robust 3D Pose EstimationCode0
Self-supervised representation learning from electroencephalography signalsCode0
TSPipe: Learn from Teacher Faster with PipelinesCode0
How to Craft Backdoors with Unlabeled Data Alone?Code0
Contrastive Self-supervised Neural Architecture SearchCode0
Blacks is to Anger as Whites is to Joy? Understanding Latent Affective Bias in Large Pre-trained Neural Language ModelsCode0
How much human-like visual experience do current self-supervised learning algorithms need in order to achieve human-level object recognition?Code0
Temporal coherence-based self-supervised learning for laparoscopic workflow analysisCode0
TTT4Rec: A Test-Time Training Approach for Rapid Adaption in Sequential RecommendationCode0
Self-supervised Representation Learning With Path Integral Clustering For Speaker DiarizationCode0
How Far Can I Go ? : A Self-Supervised Approach for Deterministic Video Depth ForecastingCode0
Temporal Cycle-Consistency LearningCode0
Homeomorphism Alignment for Unsupervised Domain AdaptationCode0
Contrastive Self-Supervised Learning for Wireless Power ControlCode0
Contrastive Self-Supervised Learning Based Approach for Patient Similarity: A Case Study on Atrial Fibrillation Detection from PPG SignalCode0
Self-supervised Rewiring of Pre-trained Speech Encoders: Towards Faster Fine-tuning with Less Labels in Speech ProcessingCode0
Test-time Training for Data-efficient UCDRCode0
BioVFM-21M: Benchmarking and Scaling Self-Supervised Vision Foundation Models for Biomedical Image AnalysisCode0
HomE: Homography-Equivariant Video Representation LearningCode0
Watch and Learn: Mapping Language and Noisy Real-world Videos with Self-supervisionCode0
Histopathology DatasetGAN: Synthesizing Large-Resolution Histopathology DatasetsCode0
Enhancing Self-Supervised Learning for Remote Sensing with Elevation Data: A Case Study with Scarce And High Level Semantic LabelsCode0
Self-supervised Semantic-driven Phoneme Discovery for Zero-resource Speech RecognitionCode0
Augmentation Component Analysis: Modeling Similarity via the Augmentation OverlapsCode0
TwinBooster: Synergising Large Language Models with Barlow Twins and Gradient Boosting for Enhanced Molecular Property PredictionCode0
Cross-Loss Influence Functions to Explain Deep Network RepresentationsCode0
Hierarchical Multi-Label Classification with Missing Information for Benthic Habitat ImageryCode0
TE-SSL: Time and Event-aware Self Supervised Learning for Alzheimer's Disease Progression AnalysisCode0
Self-supervised Shape Completion via Involution and Implicit CorrespondencesCode0
Where Did Your Model Learn That? Label-free Influence for Self-supervised LearningCode0
Hierarchical Foresight: Self-Supervised Learning of Long-Horizon Tasks via Visual Subgoal GenerationCode0
Self-Supervised Skeleton-Based Action Representation Learning: A Benchmark and BeyondCode0
Hierarchical Context Learning of object components for unsupervised semantic segmentationCode0
Self-supervised Skull Reconstruction in Brain CT Images with Decompressive CraniectomyCode0
Hiding Data Helps: On the Benefits of Masking for Sparse CodingCode0
Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View SynthesisCode0
Self-supervised Spatial-Temporal Learner for Precipitation NowcastingCode0
Self-Supervised Visual Learning by Variable Playback Speeds Prediction of a VideoCode0
Adversarial Momentum-Contrastive Pre-TrainingCode0
Heterogeneous Hypergraph Embedding for Recommendation SystemsCode0
White-Box Adversarial Defense via Self-Supervised Data EstimationCode0
Self-supervised Speech Representations Still Struggle with African American Vernacular EnglishCode0
Test-Time Domain Adaptation by Learning Domain-Aware Batch NormalizationCode0
Head-Tail Cooperative Learning Network for Unbiased Scene Graph GenerationCode0
Implicit Geometry and Interaction Embeddings Improve Few-Shot Molecular Property PredictionCode0
Using Self-Supervised Learning Can Improve Model Robustness and UncertaintyCode0
A Self-Supervised Learning Approach to Rapid Path Planning for Car-Like Vehicles Maneuvering in Urban EnvironmentCode0
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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