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 3751–3800 of 5044 papers

TitleStatusHype
Music Classification: Beyond Supervised Learning, Towards Real-world ApplicationsCode1
Self-Supervised Pre-Training for Transformer-Based Person Re-IdentificationCode1
DABS: A Domain-Agnostic Benchmark for Self-Supervised LearningCode1
Broad Adversarial Training with Data Augmentation in the Output Space—0
SSR: An Efficient and Robust Framework for Learning with Unknown Label NoiseCode1
Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment—0
Why Do Self-Supervised Models Transfer? Investigating the Impact of Invariance on Downstream TasksCode1
Benchmarking Detection Transfer Learning with Vision TransformersCode1
HoughCL: Finding Better Positive Pairs in Dense Self-supervised Learning—0
Decentralized Unsupervised Learning of Visual Representations—0
Towards Graph Self-Supervised Learning with Contrastive Adjusted Zooming—0
PyTorchVideo: A Deep Learning Library for Video UnderstandingCode2
Boosting Supervised Learning Performance with Co-training—0
Towards Fully Self-Supervised Learning of Knowledge from Unstructured Text—0
Leveraging Uni-Modal Self-Supervised Learning for Multimodal Audio-visual Speech Recognition—0
Domain-aware Self-supervised Pre-training for Weakly-supervised Meme Analysis—0
Self-supervised Semantic-driven Phoneme Discovery for Zero-resource Speech RecognitionCode0
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities—0
Self-supervised Re-renderable Facial Albedo Reconstruction from Single ImageCode1
2nd Place Solution to Facebook AI Image Similarity Challenge Matching TrackCode1
Large-Scale Hyperspectral Image Clustering Using Contrastive LearningCode0
Multimodal Generalized Zero Shot Learning for Gleason Grading using Self-Supervised Learning—0
QK Iteration: A Self-Supervised Representation Learning Algorithm for Image Similarity—0
Attention Mechanisms in Computer Vision: A SurveyCode2
Robust and Accurate Object Detection via Self-Knowledge DistillationCode0
The self-supervised spectral-spatial attention-based transformer network for automated, accurate prediction of crop nitrogen status from UAV imagery—0
Masked Autoencoders Are Scalable Vision LearnersCode1
Self-Supervised Multi-Object Tracking with Cross-Input ConsistencyCode1
A Histopathology Study Comparing Contrastive Semi-Supervised and Fully Supervised Learning—0
Membership Inference Attacks Against Self-supervised Speech ModelsCode0
Self-Supervised Audio-Visual Representation Learning with Relaxed Cross-Modal SynchronicityCode1
Hybrid BYOL-ViT: Efficient approach to deal with small datasets—0
Residual-Guided Learning Representation for Self-Supervised Monocular Depth Estimation—0
Characterizing the adversarial vulnerability of speech self-supervised learning—0
Do we still need ImageNet pre-training in remote sensing scene classification?Code1
CGCL: Collaborative Graph Contrastive Learning without Handcrafted Graph Data AugmentationsCode0
Generalized Radiograph Representation Learning via Cross-supervision between Images and Free-text Radiology ReportsCode1
Multi-Airport Delay Prediction with Transformers—0
Leveraging Time Irreversibility with Order-Contrastive Pre-training—0
Self-Supervised Radio-Visual Representation Learning for 6G Sensing—0
Distilling Word Meaning in Context from Pre-trained Language ModelsCode0
Parameter-Efficient Domain Knowledge Integration from Multiple Sources for Biomedical Pre-trained Language Models—0
On the Role of Corpus Ordering in Language Modeling—0
Towards the Generalization of Contrastive Self-Supervised LearningCode1
Learning Continuous Representation of Audio for Arbitrary Scale Super ResolutionCode1
Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation—0
Node Feature Extraction by Self-Supervised Multi-scale Neighborhood PredictionCode0
Contrastive prediction strategies for unsupervised segmentation and categorization of phonemes and wordsCode1
Barlow Graph Auto-Encoder for Unsupervised Network Embedding—0
ReSkin: versatile, replaceable, lasting tactile skinsCode1
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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