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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 801–850 of 5044 papers

TitleStatusHype
Decoupled Adversarial Contrastive Learning for Self-supervised Adversarial RobustnessCode1
Adaptive Soft Contrastive LearningCode1
Semantic-Aware Fine-Grained CorrespondenceCode1
Synthesizing Light Field Video from Monocular VideoCode1
KD-MVS: Knowledge Distillation Based Self-supervised Learning for Multi-view StereoCode1
Transfer Learning of wav2vec 2.0 for Automatic Lyric TranscriptionCode1
Video Anomaly Detection by Solving Decoupled Spatio-Temporal Jigsaw PuzzlesCode1
Fast-MoCo: Boost Momentum-based Contrastive Learning with Combinatorial PatchesCode1
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology ImagesCode1
Benchmarking Omni-Vision Representation through the Lens of Visual RealmsCode1
Synergistic Self-supervised and Quantization LearningCode1
A clinically motivated self-supervised approach for content-based image retrieval of CT liver imagesCode1
Towards Proper Contrastive Self-supervised Learning Strategies For Music Audio RepresentationCode1
Sudowoodo: Contrastive Self-supervised Learning for Multi-purpose Data Integration and PreparationCode1
Masked Surfel Prediction for Self-Supervised Point Cloud LearningCode1
Federated Self-supervised Learning for Video UnderstandingCode1
Task-oriented Self-supervised Learning for Anomaly Detection in ElectroencephalographyCode1
Masked Autoencoders in 3D Point Cloud Representation LearningCode1
Dissecting Self-Supervised Learning Methods for Surgical Computer VisionCode1
Masked Autoencoder for Self-Supervised Pre-training on Lidar Point CloudsCode1
FitHuBERT: Going Thinner and Deeper for Knowledge Distillation of Speech Self-Supervised LearningCode1
Self-Supervised Learning for Multimedia RecommendationCode1
No Reason for No Supervision: Improved Generalization in Supervised ModelsCode1
CONVIQT: Contrastive Video Quality EstimatorCode1
SSL-Lanes: Self-Supervised Learning for Motion Forecasting in Autonomous DrivingCode1
Automatic identification of segmentation errors for radiotherapy using geometric learningCode1
Self-supervised Learning in Remote Sensing: A ReviewCode1
Wiener Graph Deconvolutional Network Improves Graph Self-Supervised LearningCode1
Vision Transformer for Contrastive ClusteringCode1
SLIC: Self-Supervised Learning with Iterative Clustering for Human Action VideosCode1
Speech Quality Assessment through MOS using Non-Matching ReferencesCode1
BYOL-S: Learning Self-supervised Speech Representations by BootstrappingCode1
A Systematic Comparison of Phonetic Aware Techniques for Speech EnhancementCode1
Self-Supervised Learning of Brain Dynamics from Broad Neuroimaging DataCode1
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language ModelsCode1
Adapting Self-Supervised Vision Transformers by Probing Attention-Conditioned Masking ConsistencyCode1
Patch-level Representation Learning for Self-supervised Vision TransformersCode1
Evaluating Self-Supervised Learning for Molecular Graph EmbeddingsCode1
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
Self-Supervised Learning of Image Scale and OrientationCode1
A Simple Data Mixing Prior for Improving Self-Supervised LearningCode1
RoSGAS: Adaptive Social Bot Detection with Reinforced Self-Supervised GNN Architecture SearchCode1
SERE: Exploring Feature Self-relation for Self-supervised TransformerCode1
Masked Autoencoders are Robust Data AugmentorsCode1
CASS: Cross Architectural Self-Supervision for Medical Image AnalysisCode1
Self-supervised Learning for Human Activity Recognition Using 700,000 Person-days of Wearable DataCode1
Variable-rate hierarchical CPC leads to acoustic unit discovery in speechCode1
Poisson2Sparse: Self-Supervised Poisson Denoising From a Single ImageCode1
Rethinking and Scaling Up Graph Contrastive Learning: An Extremely Efficient Approach with Group DiscriminationCode1
Siamese Image Modeling for Self-Supervised Vision Representation 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