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 2451–2500 of 5044 papers

TitleStatusHype
A Unified Membership Inference Method for Visual Self-supervised Encoder via Part-aware CapabilityCode0
Generative-Contrastive Heterogeneous Graph Neural NetworkCode0
IWNeXt: an image-wavelet domain ConvNeXt-based network for self-supervised multi-contrast MRI reconstruction—0
Learning to Plan for Language Modeling from Unlabeled DataCode0
SelfReplay: Adapting Self-Supervised Sensory Models via Adaptive Meta-Task Replay—0
3D-Speaker-Toolkit: An Open-Source Toolkit for Multimodal Speaker Verification and Diarization—0
Patch Spatio-Temporal Relation Prediction for Video Anomaly Detection—0
MVEB: Self-Supervised Learning with Multi-View Entropy BottleneckCode0
The Bad Batches: Enhancing Self-Supervised Learning in Image Classification Through Representative Batch Curation—0
Towards Reverse-Engineering the Brain: Brain-Derived Neuromorphic Computing Approach with Photonic, Electronic, and Ionic Dynamicity in 3D integrated circuits—0
Branch-Tuning: Balancing Stability and Plasticity for Continual Self-Supervised Learning—0
ViTAR: Vision Transformer with Any Resolution—0
Noise-Robust Keyword Spotting through Self-supervised PretrainingCode0
Masked Autoencoders are PDE LearnersCode0
Boosting Few-Shot Learning with Disentangled Self-Supervised Learning and Meta-Learning for Medical Image Classification—0
Self-STORM: Deep Unrolled Self-Supervised Learning for Super-Resolution MicroscopyCode0
Self-Supervised Learning for Medical Image Data with Anatomy-Oriented Imaging Planes—0
Dyna-LfLH: Learning Agile Navigation in Dynamic Environments from Learned Hallucination—0
Connecting the Dots: Inferring Patent Phrase Similarity with Retrieved Phrase Graphs—0
L-MAE: Longitudinal masked auto-encoder with time and severity-aware encoding for diabetic retinopathy progression prediction—0
One Masked Model is All You Need for Sensor Fault Detection, Isolation and Accommodation—0
Pose-Guided Self-Training with Two-Stage Clustering for Unsupervised Landmark DiscoveryCode0
Technical Report: Masked Skeleton Sequence Modeling for Learning Larval Zebrafish Behavior Latent Embeddings—0
Boarding for ISS: Imbalanced Self-Supervised: Discovery of a Scaled Autoencoder for Mixed Tabular Datasets—0
Towards Adversarial Robustness And Backdoor Mitigation in SSLCode0
Point-DETR3D: Leveraging Imagery Data with Spatial Point Prior for Weakly Semi-supervised 3D Object Detection—0
Exploring the Task-agnostic Trait of Self-supervised Learning in the Context of Detecting Mental Disorders—0
Pose-Aware Self-Supervised Learning with Viewpoint Trajectory RegularizationCode0
Self-Supervised Backbone Framework for Diverse Agricultural Vision Tasks—0
Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential RecommendationCode0
AdaProj: Adaptively Scaled Angular Margin Subspace Projections for Anomalous Sound Detection with Auxiliary Classification TasksCode0
Exploring Green AI for Audio Deepfake DetectionCode0
Application of Tensorized Neural Networks for Cloud Classification—0
Federated Semi-supervised Learning for Medical Image Segmentation with intra-client and inter-client Consistency—0
Quantifying uncertainty in lung cancer segmentation with foundation models applied to mixed-domain datasets—0
Emotic Masked Autoencoder with Attention Fusion for Facial Expression Recognition—0
Low-Trace Adaptation of Zero-shot Self-supervised Blind Image Denoising—0
Learning Cross-view Visual Geo-localization without Ground Truth—0
Unsupervised End-to-End Training with a Self-Defined TargetCode0
Learning Useful Representations of Recurrent Neural Network Weight MatricesCode0
MLVICX: Multi-Level Variance-Covariance Exploration for Chest X-ray Self-Supervised Representation Learning—0
IPCL: Iterative Pseudo-Supervised Contrastive Learning to Improve Self-Supervised Feature RepresentationCode0
Repoformer: Selective Retrieval for Repository-Level Code Completion—0
Anomaly Detection by Adapting a pre-trained Vision Language Model—0
Data-Efficient Sleep Staging with Synthetic Time Series PretrainingCode0
Improving Acoustic Word Embeddings through Correspondence Training of Self-supervised Speech RepresentationsCode0
Self-Supervised Learning for Covariance Estimation—0
Intra-video Positive Pairs in Self-Supervised Learning for UltrasoundCode0
AACP: Aesthetics assessment of children's paintings based on self-supervised learning—0
Verification-Aided Learning of Neural Network Barrier Functions with Termination GuaranteesCode0
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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