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 1501–1550 of 5044 papers

TitleStatusHype
Multichannel AV-wav2vec2: A Framework for Learning Multichannel Multi-Modal Speech RepresentationCode0
Weakly Augmented Variational Autoencoder in Time Series Anomaly Detection—0
EAT: Self-Supervised Pre-Training with Efficient Audio TransformerCode3
Enhancing Essay Scoring with Adversarial Weights Perturbation and Metric-specific AttentionPooling—0
Exploiting Data Hierarchy as a New Modality for Contrastive Learning—0
Understanding Representation Learnability of Nonlinear Self-Supervised LearningCode0
Fus-MAE: A cross-attention-based data fusion approach for Masked Autoencoders in remote sensing—0
DiffBody: Diffusion-based Pose and Shape Editing of Human ImagesCode1
Balancing Continual Learning and Fine-tuning for Human Activity Recognition—0
Spikformer V2: Join the High Accuracy Club on ImageNet with an SNN TicketCode3
PEFT for Speech: Unveiling Optimal Placement, Merging Strategies, and Ensemble TechniquesCode0
Multimodal self-supervised learning for lesion localization—0
Zero-shot Active Learning Using Self Supervised Learning—0
Evaluating Fairness in Self-supervised and Supervised Models for Sequential Data—0
GPS-SSL: Guided Positive Sampling to Inject Prior Into Self-Supervised LearningCode0
Relating Events and Frames Based on Self-Supervised Learning and Uncorrelated Conditioning for Unsupervised Domain Adaptation—0
Freeze the backbones: A Parameter-Efficient Contrastive Approach to Robust Medical Vision-Language Pre-training—0
A Novel Transformer-Based Self-Supervised Learning Method to Enhance Photoplethysmogram Signal Artifact Detection—0
EEGPT: Pretrained Transformer for Universal and Reliable Representation of EEG SignalsCode3
An Asymmetric Augmented Self-Supervised Learning Method for Unsupervised Fine-Grained Image Hashing—0
Improving Graph Contrastive Learning via Adaptive Positive Sampling—0
Fast Adaptation for Human Pose Estimation via Meta-Optimization—0
ES3: Evolving Self-Supervised Learning of Robust Audio-Visual Speech Representations—0
Imagine Before Go: Self-Supervised Generative Map for Object Goal NavigationCode2
ShapeMatcher: Self-Supervised Joint Shape Canonicalization Segmentation Retrieval and DeformationCode1
Circuit Design and Efficient Simulation of Quantum Inner Product and Empirical Studies of Its Effect on Near-Term Hybrid Quantum-Classic Machine LearningCode0
Representing Part-Whole Hierarchies in Foundation Models by Learning Localizability Composability and Decomposability from Anatomy via Self SupervisionCode1
Self-supervised learning for skin cancer diagnosis with limited training dataCode0
Skeleton2vec: A Self-supervised Learning Framework with Contextualized Target Representations for Skeleton SequenceCode0
Masked Modeling for Self-supervised Representation Learning on Vision and BeyondCode2
SVFAP: Self-supervised Video Facial Affect PerceiverCode1
Unifying Self-Supervised Clustering and Energy-Based Models—0
Morphing Tokens Draw Strong Masked Image ModelsCode0
SSL-OTA: Unveiling Backdoor Threats in Self-Supervised Learning for Object Detection—0
Mitigating Degree Biases in Message Passing Mechanism by Utilizing Community StructuresCode1
3DTINC: Time-Equivariant Non-Contrastive Learning for Predicting Disease Progression from Longitudinal OCTs—0
BAL: Balancing Diversity and Novelty for Active LearningCode0
A Self Supervised StyleGAN for Image Annotation and Classification with Extremely Limited Labels—0
Uncertainty as a Predictor: Leveraging Self-Supervised Learning for Zero-Shot MOS Prediction—0
Self-Supervised Learning for Few-Shot Bird Sound ClassificationCode1
STRIDE: Single-video based Temporally Continuous Occlusion-Robust 3D Pose EstimationCode0
Understanding normalization in contrastive representation learning and out-of-distribution detectionCode0
TransFace: Unit-Based Audio-Visual Speech Synthesizer for Talking Head Translation—0
emotion2vec: Self-Supervised Pre-Training for Speech Emotion RepresentationCode3
Leveraging Visual Supervision for Array-based Active Speaker Detection and LocalizationCode0
Meta Transfer of Self-Supervised Knowledge: Foundation Model in Action for Post-Traumatic Epilepsy Prediction—0
SelfEEG: A Python library for Self-Supervised Learning in ElectroencephalographyCode1
Fed-QSSL: A Framework for Personalized Federated Learning under Bitwidth and Data HeterogeneityCode0
FusDom: Combining In-Domain and Out-of-Domain Knowledge for Continuous Self-Supervised LearningCode0
Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation—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