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 3701–3750 of 5044 papers

TitleStatusHype
Synergistic Effects of Knowledge Distillation and Structured Pruning for Self-Supervised Speech Models—0
SynStitch: a Self-Supervised Learning Network for Ultrasound Image Stitching Using Synthetic Training Pairs and Indirect Supervision—0
Synthetic Hard Negative Samples for Contrastive Learning—0
Synthetic Speech Source Tracing using Metric Learning—0
T3D: Advancing 3D Medical Vision-Language Pre-training by Learning Multi-View Visual Consistency—0
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities—0
TAGA: Self-supervised Learning for Template-free Animatable Gaussian Articulated Model—0
TAGA: Text-Attributed Graph Self-Supervised Learning by Synergizing Graph and Text Mutual Transformations—0
TailorMe: Self-Supervised Learning of an Anatomically Constrained Volumetric Human Shape Model—0
Taming Contrast Maximization for Learning Sequential, Low-latency, Event-based Optical Flow—0
Tandem Multitask Training of Speaker Diarisation and Speech Recognition for Meeting Transcription—0
Effective Targeted Attacks for Adversarial Self-Supervised Learning—0
Target Speaker Lipreading by Audio-Visual Self-Distillation Pretraining and Speaker Adaptation—0
Target Speech Extraction with Pre-trained Self-supervised Learning Models—0
Task-Agnostic Robust Representation Learning—0
Task-customized Masked AutoEncoder via Mixture of Cluster-conditional Experts—0
Task-Customized Self-Supervised Pre-training with Scalable Dynamic Routing—0
Task-driven Self-supervised Bi-channel Networks for Diagnosis of Breast Cancers with Mammography—0
Task-Optimized Convolutional Recurrent Networks Align with Tactile Processing in the Rodent Brain—0
Task-Oriented Low-Label Semantic Communication With Self-Supervised Learning—0
Task-Related Self-Supervised Learning for Remote Sensing Image Change Detection—0
Teaching Robots to Build Simulations of Themselves—0
Technical Report: Masked Skeleton Sequence Modeling for Learning Larval Zebrafish Behavior Latent Embeddings—0
Telextiles: End-to-end Remote Transmission of Fabric Tactile Sensation—0
Temperature-Free Loss Function for Contrastive Learning—0
Temporal-Aware Self-Supervised Learning for 3D Hand Pose and Mesh Estimation in Videos—0
Temporal Coherent Test-Time Optimization for Robust Video Classification—0
Temporal Overlapping Prediction: A Self-supervised Pre-training Method for LiDAR Moving Object Segmentation—0
Temporal Representation Learning for Stock Similarities and Its Applications in Investment Management—0
Temporal Variability and Multi-Viewed Self-Supervised Representations to Tackle the ASVspoof5 Deepfake Challenge—0
Ten Years after ImageNet: A 360° Perspective on AI—0
Terrain-Informed Self-Supervised Learning: Enhancing Building Footprint Extraction from LiDAR Data with Limited Annotations—0
TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis—0
Test-time adaptation for geospatial point cloud semantic segmentation with distinct domain shifts—0
Test-Time Adaptation for Visual Document Understanding—0
Test-Time Adaptation of 3D Point Clouds via Denoising Diffusion Models—0
Test-Time Training for Generalization under Distribution Shifts—0
Test-Time Training for Graph Neural Networks—0
Test-Time Training for Out-of-Distribution Generalization—0
Textbook Question Answering with Multi-modal Context Graph Understanding and Self-supervised Open-set Comprehension—0
Text-dependent Speaker Verification (TdSV) Challenge 2024: Challenge Evaluation Plan—0
Text-guided HuBERT: Self-Supervised Speech Pre-training via Generative Adversarial Networks—0
Text-Guided Image Invariant Feature Learning for Robust Image Watermarking—0
Text-Guided Scene Sketch-to-Photo Synthesis—0
Retro: Reusing teacher projection head for efficient embedding distillation on Lightweight Models via Self-supervised Learning—0
Text Transformations in Contrastive Self-Supervised Learning: A Review—0
InfoHier: Hierarchical Information Extraction via Encoding and Embedding—0
The Bad Batches: Enhancing Self-Supervised Learning in Image Classification Through Representative Batch Curation—0
The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning—0
The Challenges of Continuous Self-Supervised Learning—0
Show:102550
← PrevPage 75 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