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 2001–2050 of 5044 papers

TitleStatusHype
Block-to-Scene Pre-training for Point Cloud Hybrid-Domain Masked Autoencoders—0
Distributionally robust self-supervised learning for tabular dataCode0
Non-transferable Pruning—0
CSSL: Contrastive Self-Supervised Learning for Dependency Parsing on Relatively Free Word Ordered and Morphologically Rich Low Resource Languages—0
Robust infrared small target detection using self-supervised and a contrario paradigms—0
Self-Supervised Learning for Real-World Object Detection: a Survey—0
Structure-Centric Robust Monocular Depth Estimation via Knowledge Distillation—0
CUBE360: Learning Cubic Field Representation for Monocular 360 Depth Estimation for Virtual Reality—0
Wearable-Based Real-time Freezing of Gait Detection in Parkinson's Disease Using Self-Supervised Learning—0
Self-supervised inter-intra period-aware ECG representation learning for detecting atrial fibrillation—0
SkillMatch: Evaluating Self-supervised Learning of Skill Relatedness—0
Failure-Proof Non-Contrastive Self-Supervised Learning—0
Rethinking Weak-to-Strong Augmentation in Source-Free Domain Adaptive Object Detection—0
T-JEPA: Augmentation-Free Self-Supervised Learning for Tabular Data—0
Self-Supervised Anomaly Detection in the Wild: Favor Joint Embeddings Methods—0
Test-Time Adaptation for Keypoint-Based Spacecraft Pose Estimation Based on Predicted-View SynthesisCode0
Enhancing Graph Self-Supervised Learning with Graph Interplay—0
Improving Node Representation by Boosting Target-Aware Contrastive Loss—0
CUDLE: Learning Under Label Scarcity to Detect Cannabis Use in Uncontrolled Environments—0
Self-supervised Spatio-Temporal Graph Mask-Passing Attention Network for Perceptual Importance Prediction of Multi-point Tactility—0
DiffKillR: Killing and Recreating Diffeomorphisms for Cell Annotation in Dense Microscopy ImagesCode0
SynCo: Synthetic Hard Negatives in Contrastive Learning for Better Unsupervised Visual RepresentationsCode0
BiSSL: Enhancing the Alignment Between Self-Supervised Pretraining and Downstream Fine-Tuning via Bilevel Optimization—0
Decorrelation-based Self-Supervised Visual Representation Learning for Writer Identification—0
OCC-MLLM-Alpha:Empowering Multi-modal Large Language Model for the Understanding of Occluded Objects with Self-Supervised Test-Time Learning—0
SSL-NBV: A Self-Supervised-Learning-Based Next-Best-View algorithm for Efficient 3D Plant Reconstruction by a Robot—0
Meta-TTT: A Meta-learning Minimax Framework For Test-Time Training—0
On the Generalization and Causal Explanation in Self-Supervised LearningCode0
Local-to-Global Self-Supervised Representation Learning for Diabetic Retinopathy Grading—0
Contrastive Abstraction for Reinforcement Learning—0
Pre-training with Synthetic Patterns for Audio—0
Radio Foundation Models: Pre-training Transformers for 5G-based Indoor Localization—0
AfriHuBERT: A self-supervised speech representation model for African languagesCode0
Self-supervised Auxiliary Learning for Texture and Model-based Hybrid Robust and Fair Featuring in Face Analysis—0
Multi-modal Cross-domain Self-supervised Pre-training for fMRI and EEG Fusion—0
TTT4Rec: A Test-Time Training Approach for Rapid Adaption in Sequential RecommendationCode0
A3: Active Adversarial Alignment for Source-Free Domain AdaptationCode0
Localizing Memorization in SSL Vision Encoders—0
RmGPT: Rotating Machinery Generative Pretrained Model—0
SOAR: Self-supervision Optimized UAV Action Recognition with Efficient Object-Aware Pretraining—0
Packet Inspection Transformer: A Self-Supervised Journey to Unseen Malware Detection with Few Samples—0
Self-Supervised Learning of Deviation in Latent Representation for Co-speech Gesture Video Generation—0
Exploring Acoustic Similarity in Emotional Speech and Music via Self-Supervised Representations—0
Description-based Controllable Text-to-Speech with Cross-Lingual Voice Control—0
Cross-Lingual Speech Emotion Recognition: Humans vs. Self-Supervised ModelsCode0
Emotional Dimension Control in Language Model-Based Text-to-Speech: Spanning a Broad Spectrum of Human Emotions—0
EMIT- Event-Based Masked Auto Encoding for Irregular Time SeriesCode0
Trading through Earnings Seasons using Self-Supervised Contrastive Representation Learning—0
Block Expanded DINORET: Adapting Natural Domain Foundation Models for Retinal Imaging Without Catastrophic Forgetting—0
Benchmarking Domain Generalization Algorithms in Computational PathologyCode0
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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