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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 4351–4400 of 5044 papers

TitleStatusHype
Towards Zero-shot Commonsense Reasoning with Self-supervised Refinement of Language ModelsCode0
Robot Localization and Navigation through Predictive Processing using LiDAR—0
Taming Self-Supervised Learning for Presentation Attack Detection: De-Folding and De-MixingCode0
SanitAIs: Unsupervised Data Augmentation to Sanitize Trojaned Neural Networks—0
X-GOAL: Multiplex Heterogeneous Graph Prototypical Contrastive Learning—0
Self-supervised Tumor Segmentation through Layer Decomposition—0
GANSER: A Self-supervised Data Augmentation Framework for EEG-based Emotion Recognition—0
Fine-grained Hand Gesture Recognition in Multi-viewpoint Hand HygieneCode0
Training Deep Networks from Zero to Hero: avoiding pitfalls and going beyondCode0
Re-entry Prediction for Online Conversations via Self-Supervised LearningCode0
Improving Joint Learning of Chest X-Ray and Radiology Report by Word Region AlignmentCode0
LAViTeR: Learning Aligned Visual and Textual Representations Assisted by Image and Caption GenerationCode0
Resource and data efficient self supervised learning—0
Computer Vision Self-supervised Learning Methods on Time Series—0
Motifs-based Recommender System via Hypergraph Convolution and Contrastive LearningCode0
Boosting Search Engines with Interactive Agents—0
EventPoint: Self-Supervised Interest Point Detection and Description for Event-based Camera—0
Learning to Discover Reflection Symmetry via Polar Matching Convolution—0
Learning From Long-Tailed Data With Noisy Labels—0
Graph Neural Networks: Methods, Applications, and Opportunities—0
Semi-supervised learning for joint SAR and multispectral land cover classification—0
Self-Supervised Video Representation Learning with Meta-Contrastive Network—0
Concurrent Discrimination and Alignment for Self-Supervised Feature Learning—0
Topo2vec: Topography Embedding Using the Fractal EffectCode0
Self-Supervised Visual Representations Learning by Contrastive Mask Prediction—0
Self-Supervised 3D Human Pose Estimation with Multiple-View GeometryCode0
RRLFSOR: An Efficient Self-Supervised Learning Strategy of Graph Convolutional Networks—0
Investigating a Baseline Of Self Supervised Learning Towards Reducing Labeling Costs For Image Classification—0
MVCNet: Multiview Contrastive Network for Unsupervised Representation Learning for 3D CT Lesions—0
Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping—0
Collaborative Unsupervised Visual Representation Learning from Decentralized DataCode0
Focus on the Positives: Self-Supervised Learning for Biodiversity MonitoringCode0
Cervical Optical Coherence Tomography Image Classification Based on Contrastive Self-Supervised Texture LearningCode0
Self-supervised Consensus Representation Learning for Attributed GraphCode0
How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?—0
Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos—0
Self-Supervised Learning from Unlabeled Fundus Photographs Improves Segmentation of the Retina—0
Self-Supervised Learning of Depth and Ego-Motion from Video by Alternative Training and Geometric Constraints from 3D to 2D—0
Solo-learn: A Library of Self-supervised Methods for Visual Representation LearningCode0
Self-supervised Learning with Local Attention-Aware Feature—0
Self Context and Shape Prior for Sensorless Freehand 3D Ultrasound Reconstruction—0
Experimenting with Self-Supervision using Rotation Prediction for Image CaptioningCode0
Combining Probabilistic Logic and Deep Learning for Self-Supervised Learning—0
Discriminative-Generative Representation Learning for One-Class Anomaly Detection—0
An Adapter Based Pre-Training for Efficient and Scalable Self-Supervised Speech Representation Learning—0
Trip-ROMA: Self-Supervised Learning with Triplets and Random MappingsCode0
On the Memorization Properties of Contrastive Learning—0
Group Contrastive Self-Supervised Learning on Graphs—0
DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancerCode0
Bridging the Gap between Language Model and Reading Comprehension: Unsupervised MRC via Self-Supervision—0
Show:102550
← PrevPage 88 of 101Next →
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