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

Showing 651700 of 5044 papers

TitleStatusHype
CUTS: A Deep Learning and Topological Framework for Multigranular Unsupervised Medical Image SegmentationCode1
CutPaste: Self-Supervised Learning for Anomaly Detection and LocalizationCode1
D2C: Diffusion-Decoding Models for Few-Shot Conditional GenerationCode1
CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from ImageCode1
Adversarial Masking for Self-Supervised LearningCode1
DAS-N2N: Machine learning Distributed Acoustic Sensing (DAS) signal denoising without clean dataCode1
CARLANE: A Lane Detection Benchmark for Unsupervised Domain Adaptation from Simulation to multiple Real-World DomainsCode1
data2vec-aqc: Search for the right Teaching Assistant in the Teacher-Student training setupCode1
3D Object Detection with a Self-supervised Lidar Scene Flow BackboneCode1
Data-Centric Learning from Unlabeled Graphs with Diffusion ModelCode1
A Review on Self-Supervised Learning for Time Series Anomaly Detection: Recent Advances and Open ChallengesCode1
CASS: Cross Architectural Self-Supervision for Medical Image AnalysisCode1
Consistency-based Self-supervised Learning for Temporal Anomaly LocalizationCode1
Improving Self-Supervised Learning by Characterizing Idealized RepresentationsCode1
GraphAlign: Pretraining One Graph Neural Network on Multiple Graphs via Feature AlignmentCode1
COSMOS: Catching Out-of-Context Misinformation with Self-Supervised LearningCode1
Adversarial Self-Supervised Contrastive LearningCode1
Container: Context Aggregation NetworksCode1
A Discrepancy Aware Framework for Robust Anomaly DetectionCode1
Causal Unsupervised Semantic SegmentationCode1
GrainSpace: A Large-scale Dataset for Fine-grained and Domain-adaptive Recognition of Cereal GrainsCode1
Detecting Backdoors in Pre-trained EncodersCode1
CCC-wav2vec 2.0: Clustering aided Cross Contrastive Self-supervised learning of speech representationsCode1
CCGL: Contrastive Cascade Graph LearningCode1
A Self-Correcting Sequential RecommenderCode1
CCVS: Context-aware Controllable Video SynthesisCode1
CDFSL-V: Cross-Domain Few-Shot Learning for VideosCode1
Deep learning powered real-time identification of insects using citizen science dataCode1
Graph Barlow Twins: A self-supervised representation learning framework for graphsCode1
ECONET: Effective Continual Pretraining of Language Models for Event Temporal ReasoningCode1
Internet Explorer: Targeted Representation Learning on the Open WebCode1
Deep Unfolded Tensor Robust PCA with Self-supervised LearningCode1
A Self-Supervised Gait Encoding Approach with Locality-Awareness for 3D Skeleton Based Person Re-IdentificationCode1
Defending Against Patch-based Backdoor Attacks on Self-Supervised LearningCode1
Intrinsically Motivated Goal Exploration Processes with Automatic Curriculum LearningCode1
Discriminative and Consistent Representation DistillationCode1
DeiT III: Revenge of the ViTCode1
Change-Aware Sampling and Contrastive Learning for Satellite ImagesCode1
DeLoRes: Decorrelating Latent Spaces for Low-Resource Audio Representation LearningCode1
Channel-Wise Attention-Based Network for Self-Supervised Monocular Depth EstimationCode1
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation OverlapCode1
Mitigating Memorization of Noisy Labels via Regularization between RepresentationsCode1
An Embarrassingly Simple Backdoor Attack on Self-supervised LearningCode1
Denoised Self-Augmented Learning for Social RecommendationCode1
Charting the Right Manifold: Manifold Mixup for Few-shot LearningCode1
Chasing Clouds: Differentiable Volumetric Rasterisation of Point Clouds as a Highly Efficient and Accurate Loss for Large-Scale Deformable 3D RegistrationCode1
ChemBERTa-2: Towards Chemical Foundation ModelsCode1
A self-supervised learning strategy for postoperative brain cavity segmentation simulating resectionsCode1
Graph Contrastive Learning AutomatedCode1
GMML is All you NeedCode1
Show:102550
← PrevPage 14 of 101Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Pretraining: NoneImages & Text57.5Unverified
2Pretraining: ShEDImages & Text54.3Unverified
3Pretraining: e-MixImages & Text48.9Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50Accuracy91.7Unverified
2ResNet18Accuracy91.02Unverified
3MV-MRAccuracy89.67Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy93.89Unverified
2ResNet18average top-1 classification accuracy92.58Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy72.51Unverified
2ResNet18average top-1 classification accuracy69.31Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet50)Top-1 Accuracy82.64Unverified
2CorInfomax (ResNet18)Top-1 Accuracy80.48Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet50average top-1 classification accuracy51.84Unverified
2ResNet18average top-1 classification accuracy51.67Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet18)Top-1 Accuracy93.18Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet18)Top-1 Accuracy71.61Unverified
#ModelMetricClaimedVerifiedStatus
1Hybrid BYOL-S/CvTAccuracy67.2Unverified
#ModelMetricClaimedVerifiedStatus
1CorInfomax (ResNet50)Top-1 Accuracy54.86Unverified