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 4201–4250 of 5044 papers

TitleStatusHype
Evaluating the Robustness of Self-Supervised Learning in Medical Imaging—0
Using Self-Supervised Auxiliary Tasks to Improve Fine-Grained Facial Representation—0
Waste detection in Pomerania: non-profit project for detecting waste in environmentCode1
Electrocardio Panorama: Synthesizing New ECG Views with Self-supervisionCode1
20-fold Accelerated 7T fMRI Using Referenceless Self-Supervised Deep Learning Reconstruction—0
When Does Contrastive Visual Representation Learning Work?—0
Task-Related Self-Supervised Learning for Remote Sensing Image Change Detection—0
Semantic Distribution-aware Contrastive Adaptation for Semantic SegmentationCode1
VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised LearningCode1
Self-Supervised Learning with Swin TransformersCode1
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning—0
Salient Objects in ClutterCode1
Self-Supervised Multi-Frame Monocular Scene FlowCode1
Self-Supervised Learning from Automatically Separated Sound ScenesCode1
Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation—0
SUPERB: Speech processing Universal PERformance BenchmarkCode1
On Feature Decorrelation in Self-Supervised LearningCode1
Hyperspherically Regularized Networks for Self-Supervision—0
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual RepresentationsCode0
Emerging Properties in Self-Supervised Vision TransformersCode1
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis—0
Shot Contrastive Self-Supervised Learning for Scene Boundary Detection—0
A Note on Connecting Barlow Twins with Negative-Sample-Free Contrastive LearningCode1
Self-supervised Spatial Reasoning on Multi-View Line DrawingsCode1
Multimodal Clustering Networks for Self-supervised Learning from Unlabeled VideosCode1
Towards Good Practices for Efficiently Annotating Large-Scale Image Classification DatasetsCode1
How Well Does Self-Supervised Pre-Training Perform with Streaming Data?—0
LeBenchmark: A Reproducible Framework for Assessing Self-Supervised Representation Learning from SpeechCode1
Inductive biases and Self Supervised Learning in modelling a physical heating systemCode0
Self-Supervised Learning from Semantically Imprecise Data—0
VATT: Transformers for Multimodal Self-Supervised Learning from Raw Video, Audio and TextCode1
SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI DataCode0
On the Impact of Word Error Rate on Acoustic-Linguistic Speech Emotion Recognition: An Update for the Deep Learning Era—0
Generative Transformer for Accurate and Reliable Salient Object DetectionCode1
Distill on the Go: Online knowledge distillation in self-supervised learningCode1
Fine-grained Anomaly Detection via Multi-task Self-Supervision—0
Self-supervised Representation Learning With Path Integral Clustering For Speaker DiarizationCode0
DisCo: Remedy Self-supervised Learning on Lightweight Models with Distilled Contrastive LearningCode1
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD DatasetCode1
Solving Inefficiency of Self-supervised Representation LearningCode1
Color Variants Identification in Fashion e-commerce via Contrastive Self-Supervised Representation Learning—0
A Surface Geometry Model for LiDAR Depth CompletionCode1
AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models—0
Pareto Self-Supervised Training for Few-Shot Learning—0
Conditional independence for pretext task selection in Self-supervised speech representation learningCode0
Contrastive Learning with Stronger AugmentationsCode1
Self-supervised Learning of 3D Object Understanding by Data Association and Landmark Estimation for Image Sequence—0
Self-Supervised Learning of Remote Sensing Scene Representations Using Contrastive Multiview CodingCode1
K-PLUG: Knowledge-injected Pre-trained Language Model for Natural Language Understanding and Generation in E-CommerceCode1
CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge DistillationCode0
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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