SOTAVerified

Unsupervised Pre-training

Pre-training a neural network using unsupervised (self-supervised) auxiliary tasks on unlabeled data.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 265 papers

TitleStatusHype
Bag of Tricks and A Strong baseline for Image Copy DetectionCode1
D^2LV: A Data-Driven and Local-Verification Approach for Image Copy DetectionCode1
Performance-Efficiency Trade-offs in Unsupervised Pre-training for Speech RecognitionCode1
RandomRooms: Unsupervised Pre-training from Synthetic Shapes and Randomized Layouts for 3D Object DetectionCode1
PEBBLE: Feedback-Efficient Interactive Reinforcement Learning via Relabeling Experience and Unsupervised Pre-trainingCode1
Exploring the Limits of Out-of-Distribution DetectionCode1
Initialization and Regularization of Factorized Neural LayersCode1
Patient Contrastive Learning: a Performant, Expressive, and Practical Approach to ECG ModelingCode1
Pre-training strategies and datasets for facial representation learningCode1
Seasonal Contrast: Unsupervised Pre-Training from Uncurated Remote Sensing DataCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
115RDLsAccuracy (%)95—Unverified
29RDLsAccuracy (%)94—Unverified
33 RMDLAccuracy (%)93—Unverified
4CNNAccuracy (%)73—Unverified
5RMDLAccuracy (%)0.1—Unverified
#ModelMetricClaimedVerifiedStatus
1RMDL (30 RDLs)Sensitivity (VEB)90.69—Unverified
2Sensitivity89.1—Unverified
3RMDL 3 RDLsSensitivity0.87—Unverified