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 1451–1500 of 5044 papers

TitleStatusHype
Decorrelation-based Self-Supervised Visual Representation Learning for Writer Identification—0
BarlowTwins-CXR : Enhancing Chest X-Ray abnormality localization in heterogeneous data with cross-domain self-supervised learning—0
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning—0
An Autoencoder-based Snow Drought Index—0
Adaptive Memory Networks with Self-supervised Learning for Unsupervised Anomaly Detection—0
HASRD: Hierarchical Acoustic and Semantic Representation Disentanglement—0
HealNet -- Self-Supervised Acute Wound Heal-Stage Classification—0
Debiased-CAM to mitigate image perturbations with faithful visual explanations of machine learning—0
Barlow Graph Auto-Encoder for Unsupervised Network Embedding—0
DDOS: A MOS Prediction Framework utilizing Domain Adaptive Pre-training and Distribution of Opinion Scores—0
Balancing Continual Learning and Fine-tuning for Human Activity Recognition—0
DCELANM-Net:Medical Image Segmentation based on Dual Channel Efficient Layer Aggregation Network with Learner—0
3D Cloud reconstruction through geospatially-aware Masked Autoencoders—0
Data Scarcity in Recommendation Systems: A Survey—0
Data-Limited Tissue Segmentation using Inpainting-Based Self-Supervised Learning—0
HandMIM: Pose-Aware Self-Supervised Learning for 3D Hand Mesh Estimation—0
HarmonyIQA: Pioneering Benchmark and Model for Image Harmonization Quality Assessment—0
Data Generation for Satellite Image Classification Using Self-Supervised Representation Learning—0
From Handheld to Unconstrained Object Detection: a Weakly-supervised On-line Learning Approach—0
Balanced Deep CCA for Bird Vocalization Detection—0
Hallucination Improves the Performance of Unsupervised Visual Representation Learning—0
Data-efficient Event Camera Pre-training via Disentangled Masked Modeling—0
Data-Efficient Contrastive Learning by Differentiable Hard Sample and Hard Positive Pair Generation—0
Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation—0
HeAR -- Health Acoustic Representations—0
Data-driven grapheme-to-phoneme representations for a lexicon-free text-to-speech—0
Knowledge Distillation for Human Action Anticipation—0
Data Collection-free Masked Video Modeling—0
Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy—0
An Asymmetric Augmented Self-Supervised Learning Method for Unsupervised Fine-Grained Image Hashing—0
A Theoretical Characterization of Optimal Data Augmentations in Self-Supervised Learning—0
Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy—0
Multi-Variant Consistency based Self-supervised Learning for Robust Automatic Speech Recognition—0
An ASR-free Fluency Scoring Approach with Self-Supervised Learning—0
Adaptive Crowdsourcing Via Self-Supervised Learning—0
Backdoor Attacks in the Supply Chain of Masked Image Modeling—0
An Analysis of Linear Complexity Attention Substitutes with BEST-RQ—0
D2SA: Dual-Stage Distribution and Slice Adaptation for Efficient Test-Time Adaptation in MRI Reconstruction—0
CycleCL: Self-supervised Learning for Periodic Videos—0
AWEncoder: Adversarial Watermarking Pre-trained Encoders in Contrastive Learning—0
Analyzing the factors affecting usefulness of Self-Supervised Pre-trained Representations for Speech Recognition—0
Abnormality-Driven Representation Learning for Radiology Imaging—0
CycAs: Self-supervised Cycle Association for Learning Re-identifiable Descriptions—0
Avoid Overthinking in Self-Supervised Models for Speech Recognition—0
AV-Lip-Sync+: Leveraging AV-HuBERT to Exploit Multimodal Inconsistency for Video Deepfake Detection—0
Analyzing Speech Unit Selection for Textless Speech-to-Speech Translation—0
Custom Object Detection via Multi-Camera Self-Supervised Learning—0
Curriculum Learning Meets Weakly Supervised Modality Correlation Learning—0
Curator: Creating Large-Scale Curated Labelled Datasets using Self-Supervised Learning—0
CUDLE: Learning Under Label Scarcity to Detect Cannabis Use in Uncontrolled Environments—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