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 4501–4550 of 5044 papers

TitleStatusHype
Improved Simultaneous Multi-Slice Functional MRI Using Self-supervised Deep Learning—0
Exploiting Audio-Visual Consistency with Partial Supervision for Spatial Audio Generation—0
With a Little Help from My Friends: Nearest-Neighbor Contrastive Learning of Visual RepresentationsCode0
Hyperspherically Regularized Networks for Self-Supervision—0
Shot Contrastive Self-Supervised Learning for Scene Boundary Detection—0
Medical Transformer: Universal Brain Encoder for 3D MRI Analysis—0
How Well Does Self-Supervised Pre-Training Perform with Streaming Data?—0
Inductive biases and Self Supervised Learning in modelling a physical heating systemCode0
Self-Supervised Learning from Semantically Imprecise Data—0
SKID: Self-Supervised Learning for Knee Injury Diagnosis from MRI DataCode0
Fine-grained Anomaly Detection via Multi-task Self-Supervision—0
On the Impact of Word Error Rate on Acoustic-Linguistic Speech Emotion Recognition: An Update for the Deep Learning Era—0
Self-supervised Representation Learning With Path Integral Clustering For Speaker DiarizationCode0
Color Variants Identification in Fashion e-commerce via Contrastive Self-Supervised Representation Learning—0
Pareto Self-Supervised Training for Few-Shot Learning—0
AMMU : A Survey of Transformer-based Biomedical Pretrained Language Models—0
Conditional independence for pretext task selection in Self-supervised speech representation learningCode0
Self-supervised Learning of 3D Object Understanding by Data Association and Landmark Estimation for Image Sequence—0
Interpretability-Driven Sample Selection Using Self Supervised Learning For Disease Classification And Segmentation—0
CXR Segmentation by AdaIN-based Domain Adaptation and Knowledge DistillationCode0
A Learnable Self-supervised Task for Unsupervised Domain Adaptation on Point Clouds—0
Stereo Matching by Self-supervision of Multiscopic Vision—0
Multiple Object Tracking with Correlation Learning—0
Representative & Fair Synthetic Data—0
Self-Supervised Learning for Gastritis Detection with Gastric X-ray Images—0
Strumming to the Beat: Audio-Conditioned Contrastive Video Textures—0
Self-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs—0
Efficient Personalized Speech Enhancement through Self-Supervised Learning—0
Personalized Speech Enhancement through Self-Supervised Data Augmentation and Purification—0
Action Shuffle Alternating Learning for Unsupervised Action Segmentation—0
Conv1D Energy-Aware Path Planner for Mobile Robots in Unstructured Environments—0
Robust wav2vec 2.0: Analyzing Domain Shift in Self-Supervised Pre-Training—0
Self-supervised Motion Learning from Static Images—0
Keep Learning: Self-supervised Meta-learning for Learning from Inference—0
Joint Learning of Neural Transfer and Architecture Adaptation for Image Recognition—0
On the Origin of Species of Self-Supervised Learning—0
Benchmarking Representation Learning for Natural World Image CollectionsCode0
Source-Free Domain Adaptation for Semantic Segmentation—0
Category-Adaptive Domain Adaptation for Semantic Segmentation—0
Tasting the cake: evaluating self-supervised generalization on out-of-distribution multimodal MRI dataCode0
Robust Audio-Visual Instance Discrimination—0
Classification of Seeds using Domain Randomization on Self-Supervised Learning Frameworks—0
Towards High Fidelity Monocular Face Reconstruction with Rich Reflectance using Self-supervised Learning and Ray Tracing—0
Friends and Foes in Learning from Noisy Labels—0
Representation Learning by Ranking under multiple tasks—0
Contrastive Domain Adaptation—0
Self-Supervised Learning in Multi-Task Graphs through Iterative Consensus ShiftCode0
Unsupervised Document Embedding via Contrastive Augmentation—0
Residual Energy-Based Models for End-to-End Speech Recognition—0
Learning Graph Representation by Aggregating Subgraphs via Mutual Information Maximization—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