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 4851–4900 of 5044 papers

TitleStatusHype
Self-Supervised Learning of Generative Spin-Glasses with Normalizing FlowsCode0
Learning Compound Tasks without Task-specific Knowledge via Imitation and Self-supervised Learning—0
Test-Time Training for Generalization under Distribution Shifts—0
Conditional Augmentation for Generative Modeling—0
A simple baseline for domain adaptation using rotation prediction—0
Image Enhanced Rotation Prediction for Self-Supervised Learning—0
Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model—0
AeroRIT: A New Scene for Hyperspectral Image AnalysisCode1
Self-Supervised Learning of Physics-Guided Reconstruction Neural Networks without Fully-Sampled Reference DataCode0
Multimodal Self-Supervised Learning for Medical Image Analysis—0
To Balance or Not to Balance: A Simple-yet-Effective Approach for Learning with Long-Tailed Distributions—0
Self-supervised Object Motion and Depth Estimation from Video—0
Self-Supervised 3D Keypoint Learning for Ego-motion EstimationCode0
Self-Supervised Contextual Language Representation of Radiology Reports to Improve the Identification of Communication Urgency—0
Self-Supervised Learning of Video-Induced Visual Invariances—0
Self-Supervised Learning of Pretext-Invariant RepresentationsCode1
Exploiting Motion Information from Unlabeled Videos for Static Image Action Recognition—0
Self-Supervised Learning by Cross-Modal Audio-Video ClusteringCode0
Invenio: Discovering Hidden Relationships Between Tasks/Domains Using Structured Meta Learning—0
SelfVIO: Self-Supervised Deep Monocular Visual-Inertial Odometry and Depth Estimation—0
Self-supervised Learning of 3D Objects from Natural Images—0
AETv2: AutoEncoding Transformations for Self-Supervised Representation Learning by Minimizing Geodesic Distances in Lie Groups—0
Self-supervised Adversarial TrainingCode0
Self-Supervised Learning For Few-Shot Image ClassificationCode0
Self-Supervised Learning of State Estimation for Manipulating Deformable Linear Objects—0
Self-labelling via simultaneous clustering and representation learningCode1
Self-supervised representation learning from electroencephalography signalsCode0
Unsupervised Domain Adaptation of Contextual Embeddings for Low-Resource Duplicate Question Detection—0
Self-supervised learning of class embeddings from video—0
PRNet: Self-Supervised Learning for Partial-to-Partial RegistrationCode1
Learning audio representations via phase prediction—0
Self-supervised Learning of Detailed 3D Face ReconstructionCode0
Deep Reinforcement Learning for Synthesizing Functions in Higher-Order LogicCode0
SPICE: Self-supervised Pitch Estimation—0
Domain Bridge for Unpaired Image-to-Image Translation and Unsupervised Domain Adaptation—0
Self-supervised classification of dynamic obstacles using the temporal information provided by videos—0
Self-Supervised Physics-Based Deep Learning MRI Reconstruction Without Fully-Sampled DataCode0
Modeling Disease Progression In Retinal OCTs With Longitudinal Self-Supervised Learning—0
Adversarial Skill Networks: Unsupervised Robot Skill Learning from VideoCode0
Label-efficient audio classification through multitask learning and self-supervision—0
Animating Landscape: Self-Supervised Learning of Decoupled Motion and Appearance for Single-Image Video SynthesisCode1
Self-supervised Learning for ECG-based Emotion RecognitionCode1
Self-supervised Label Augmentation via Input TransformationsCode0
vq-wav2vec: Self-Supervised Learning of Discrete Speech RepresentationsCode1
FetusMap: Fetal Pose Estimation in 3D Ultrasound—0
Learning Visual Affordances with Target-Orientated Deep Q-Network to Grasp Objects by Harnessing Environmental Fixtures—0
Learning to Generalize One Sample at a Time with Self-Supervision—0
When Does Self-supervision Improve Few-shot Learning?Code0
Learning event representations for temporal segmentation of image sequences by dynamic graph embedding—0
FisheyeDistanceNet: Self-Supervised Scale-Aware Distance Estimation using Monocular Fisheye Camera for Autonomous Driving—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