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 401–450 of 5044 papers

TitleStatusHype
DISP6D: Disentangled Implicit Shape and Pose Learning for Scalable 6D Pose EstimationCode1
Disjoint Masking with Joint Distillation for Efficient Masked Image ModelingCode1
Coreset Sampling from Open-Set for Fine-Grained Self-Supervised LearningCode1
Distance-wise Prototypical Graph Neural Network in Node Imbalance ClassificationCode1
A Survey on Self-Supervised Graph Foundation Models: Knowledge-Based PerspectiveCode1
A Symbolic Character-Aware Model for Solving Geometry ProblemsCode1
A Hybrid Self-Supervised Learning Framework for Vertical Federated LearningCode1
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
Contrastive Self-Supervised Learning for Commonsense ReasoningCode1
DEER: Descriptive Knowledge Graph for Explaining Entity RelationshipsCode1
DocMAE: Document Image Rectification via Self-supervised Representation LearningCode1
Does Learning from Decentralized Non-IID Unlabeled Data Benefit from Self Supervision?Code1
Domain Knowledge-Informed Self-Supervised Representations for Workout Form AssessmentCode1
Do SSL Models Have Déjà Vu? A Case of Unintended Memorization in Self-supervised LearningCode1
A Self-Correcting Sequential RecommenderCode1
Benchmarking Embedding Aggregation Methods in Computational Pathology: A Clinical Data PerspectiveCode1
Dual Intents Graph Modeling for User-centric Group DiscoveryCode1
ATST: Audio Representation Learning with Teacher-Student TransformerCode1
Contrastive Self-supervised Sequential Recommendation with Robust AugmentationCode1
Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and wordsCode1
Attention Distillation: self-supervised vision transformer students need more guidanceCode1
AVF-MAE++: Scaling Affective Video Facial Masked Autoencoders via Efficient Audio-Visual Self-Supervised LearningCode1
Contrastive Representation Learning for Gaze EstimationCode1
Self-supervised Spatial Reasoning on Multi-View Line DrawingsCode1
CorruptEncoder: Data Poisoning based Backdoor Attacks to Contrastive LearningCode1
Attentive Symmetric Autoencoder for Brain MRI SegmentationCode1
Contrastive Learning with Cross-Modal Knowledge Mining for Multimodal Human Activity RecognitionCode1
Audio-Adaptive Activity Recognition Across Video DomainsCode1
Active Learning Through a Covering LensCode1
BasisFormer: Attention-based Time Series Forecasting with Learnable and Interpretable BasisCode1
Adversarial Self-Supervised Contrastive LearningCode1
Contrastive Learning with Stronger AugmentationsCode1
Contrastive Learning with Boosted MemorizationCode1
Efficient Adapter Transfer of Self-Supervised Speech Models for Automatic Speech RecognitionCode1
Contrastive Learning with Synthetic PositivesCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
Efficient Self-supervised Learning with Contextualized Target Representations for Vision, Speech and LanguageCode1
Efficient Self-Supervised Video Hashing with Selective State SpacesCode1
AASAE: Augmentation-Augmented Stochastic AutoencodersCode1
Benchmarking and Improving Large Vision-Language Models for Fundamental Visual Graph Understanding and ReasoningCode1
M3-Jepa: Multimodal Alignment via Multi-directional MoE based on the JEPA frameworkCode1
Augmentation-Free Self-Supervised Learning on GraphsCode1
3D Object Detection with a Self-supervised Lidar Scene Flow BackboneCode1
Contrastive learning of global and local features for medical image segmentation with limited annotationsCode1
Contrastive Learning Inverts the Data Generating ProcessCode1
Augmenting Reinforcement Learning with Transformer-based Scene Representation Learning for Decision-making of Autonomous DrivingCode1
scSSL-Bench: Benchmarking Self-Supervised Learning for Single-Cell DataCode1
Benchmarking Omni-Vision Representation through the Lens of Visual RealmsCode1
AMMUS : A Survey of Transformer-based Pretrained Models in Natural Language ProcessingCode1
Adversarial Masking for Self-Supervised LearningCode1
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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