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 2951–3000 of 5044 papers

TitleStatusHype
Improving Image Clustering through Sample Ranking and Its Application to remote--sensing imagesCode0
Dive into Self-Supervised Learning for Medical Image Analysis: Data, Models and TasksCode1
Controllable Face Manipulation and UV Map Generation by Self-supervised Learning—0
Self-supervised Learning for Unintentional Action Prediction—0
Deep Attentive Belief Propagation: Integrating Reasoning and Learning for Solving Constraint Optimization Problems—0
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image SegmentationCode1
Self-supervised Learning for Clustering of Wireless Spectrum ActivityCode0
Pretraining the Vision Transformer using self-supervised methods for vision based Deep Reinforcement LearningCode0
Cross-domain Voice Activity Detection with Self-Supervised Representations—0
WeLM: A Well-Read Pre-trained Language Model for Chinese—0
Locally Constrained Representations in Reinforcement Learning—0
NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex ScenesCode1
Attentive Symmetric Autoencoder for Brain MRI SegmentationCode1
The Geometry of Self-supervised Learning Models and its Impact on Transfer Learning—0
On PAC Learning Halfspaces in Non-interactive Local Privacy Model with Public Unlabeled Data—0
Few-Shot Classification with Contrastive Learning—0
Self-supervised learning of hologram reconstruction using physics consistency—0
Modeling Multiple Views via Implicitly Preserving Global Consistency and Local ComplementarityCode0
MetaMask: Revisiting Dimensional Confounder for Self-Supervised LearningCode1
Self-Supervised Learning of Phenotypic Representations from Cell Images with Weak LabelsCode1
Spatial-then-Temporal Self-Supervised Learning for Video CorrespondenceCode1
Enhance the Visual Representation via Discrete Adversarial TrainingCode0
Graph Contrastive Learning with Cross-view Reconstruction—0
Exploring StyleGAN Latent Space for Face Alignment with Limited Training Data—0
Self-Supervised Learning with an Information Maximization CriterionCode1
Self-Relation Attention and Temporal Awareness for Emotion Recognition via Vocal BurstCode0
LAVIS: A Library for Language-Vision Intelligence—0
Multi-Modal Masked Autoencoders for Medical Vision-and-Language Pre-TrainingCode1
Improving Self-Supervised Learning by Characterizing Idealized RepresentationsCode1
Just Noticeable Difference Modeling for Face Recognition System—0
SeRP: Self-Supervised Representation Learning Using Perturbed Point Clouds—0
Graph Neural Networks for Molecules—0
OpenMixup: Open Mixup Toolbox and Benchmark for Visual Representation Learning—0
Self-supervised Learning for Panoptic Segmentation of Multiple Fruit Flower SpeciesCode0
Self-supervised Learning for Heterogeneous Graph via Structure Information based on Metapath—0
SSL-WM: A Black-Box Watermarking Approach for Encoders Pre-trained by Self-supervised LearningCode0
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypesCode0
Improving Self-supervised Learning for Out-of-distribution Task via Auxiliary ClassifierCode0
MimCo: Masked Image Modeling Pre-training with Contrastive Teacher—0
Robust and Efficient Imbalanced Positive-Unlabeled Learning with Self-supervisionCode0
Continual Learning, Fast and SlowCode1
Real-Time Cattle Interaction Recognition via Triple-stream Network—0
ChemBERTa-2: Towards Chemical Foundation ModelsCode1
Federated Transfer Learning with Multimodal Data—0
Imaging with Equivariant Deep Learning—0
Multi-modal Masked Autoencoders Learn Compositional Histopathological RepresentationsCode1
Feature diversity in self-supervised learning—0
Detection of diabetic retinopathy using longitudinal self-supervised learning—0
IMG2IMU: Translating Knowledge from Large-Scale Images to IMU Sensing Applications—0
Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction—0
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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